Publications
2025
Translating Simulation Images to X-Ray Images via Multi-scale Semantic Matching
Kang, J., Jianu, T., Huang, B., Bhattarai, B., Le, N., Coenen, F., & Nguyen, A. (2025). Translating Simulation Images to X-Ray Images via Multi-scale Semantic Matching. In Lecture Notes in Computer Science (pp. 95-104). Springer Nature Switzerland. doi:10.1007/978-3-031-73748-0_10
2024
Corrigendum to “Social media sentiment analysis and opinion mining in public security: Taxonomy, trend analysis, issues and future directions” [J. King Saud Univ. – Comput. Inform. Sci. 35(9) (2023) 101776]
Suhaimin, M. S. M., Hijazi, M. H. A., Moung, E. G., Nohuddin, P. N. E., Chua, S., & Coenen, F. (2024). Corrigendum to “Social media sentiment analysis and opinion mining in public security: Taxonomy, trend analysis, issues and future directions” [J. King Saud Univ. – Comput. Inform. Sci. 35(9) (2023) 101776]. Journal of King Saud University - Computer and Information Sciences, 36(6), 102121. doi:10.1016/j.jksuci.2024.102121
Artificial intelligence-enhanced electrocardiogram analysis for identifying cardiac autonomic neuropathy in patients with diabetes
Irlik, K., Aldosari, H., Hendel, M., Piaśnik, J., Kulpa, J., Ignacy, P., . . . Nabrdalik, K. (2024). Artificial intelligence-enhanced electrocardiogram analysis for identifying cardiac autonomic neuropathy in patients with diabetes. Diabetes, Obesity and Metabolism: a journal of pharmacology and therapeutics.
Editorial for Special Issue on “Expert decision making for data analytics with applications”
Yuen, K. K. F., Leu, J. -S., Ishizaka, A., Tawfik, H., & Coenen, F. (2024). Editorial for Special Issue on “Expert decision making for data analytics with applications”. Applied Soft Computing, 155, 111480. doi:10.1016/j.asoc.2024.111480
Predicting Post Myocardial Infarction Complication: A Study Using Dual-Modality and Imbalanced Flow Cytometry Data
ALdausari, N., Coenen, F., Nguyen, A., & Shantsila, E. (2024). Predicting Post Myocardial Infarction Complication: A Study Using Dual-Modality and Imbalanced Flow Cytometry Data. In Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (pp. 81-90). SCITEPRESS - Science and Technology Publications. doi:10.5220/0012998300003838
Springback Prediction Using Gated Recurrent Unit and Data Augmentation
Chen, D., Coenen, F., Hai, Y., Oscoz, M. P., & Nguyen, A. (2024). Springback Prediction Using Gated Recurrent Unit and Data Augmentation. In Unknown Conference (pp. 1-13). Springer Nature Singapore. doi:10.1007/978-981-99-8498-5_1
2023
Artificial intelligence-enhanced electrocardiogram analysis for identifying cardiac autonomic neuropathy in patients with diabetes
Deep ensemble learning for high-dimensional subsurface fluid flow modeling
Choubineh, A., Chen, J., Wood, D. A., Coenen, F., & Ma, F. (2023). Deep ensemble learning for high-dimensional subsurface fluid flow modeling. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 126. doi:10.1016/j.engappai.2023.106968
An interpretable framework for sleep posture change detection and postural inactivity segmentation using wrist kinematics.
Elnaggar, O., Arelhi, R., Coenen, F., Hopkinson, A., Mason, L., & Paoletti, P. (2023). An interpretable framework for sleep posture change detection and postural inactivity segmentation using wrist kinematics.. Scientific reports, 13(1), 18027. doi:10.1038/s41598-023-44567-9
Social Media Sentiment Analysis and Opinion Mining in Public Security: Taxonomy, Trend Analysis, Issues and Future Directions
Hijazi, A., & Coenen, F. (2023). Social Media Sentiment Analysis and Opinion Mining in Public Security: Taxonomy, Trend Analysis, Issues and Future Directions. Journal of King Saud University: Computer and Information Sciences.
RgnTX: colocalization analysis of transcriptome elements in the presence of isoform heterogeneity and ambiguity
Coenen, F., Wang, Y., Meng, J., Wei, Z., & Su, J. (2023). RgnTX: colocalization analysis of transcriptome elements in the presence of isoform heterogeneity and ambiguity. Computational and Structural Biotechnology Journal. doi:10.1016/j.csbj.2023.08.021
Pathology Data Prioritisation: A Study of Using Multi-variate Time Series
Qi, J., Burnside, G., & Coenen, F. (2023). Pathology Data Prioritisation: A Study of Using Multi-variate Time Series. In Unknown Conference (pp. 1-20). Springer International Publishing. doi:10.1007/978-3-031-35924-8_1
Sleep posture one-shot learning framework based on extremity joint kinematics: In-silico and in-vivo case studies
Elnaggar, O., Coenen, F., Hopkinson, A., Mason, L., & Paoletti, P. (2023). Sleep posture one-shot learning framework based on extremity joint kinematics: In-silico and in-vivo case studies. INFORMATION FUSION, 95, 215-236. doi:10.1016/j.inffus.2023.02.003
A Robust Framework of Chromosome Straightening With Vit-Patch Gan
Song, S., Wang, J., Cheng, F., Cao, Q., Zuo, Y., Lei, Y., . . . Su, J. (2023). A Robust Framework of Chromosome Straightening With Vit-Patch Gan. In 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI) (pp. 1-5). IEEE. doi:10.1109/isbi53787.2023.10230388
Triple-kernel Gated Attention-based Multiple Instance Learning with Contrastive Learning for Medical Image Analysis
Coenen, F., Ye, R., Hu, H., Thiyagalingam, J., & Su, J. (2023). Triple-kernel Gated Attention-based Multiple Instance Learning with Contrastive Learning for Medical Image Analysis. Applied Intelligence.
Applying Monte Carlo Dropout to Quantify the Uncertainty of Skip Connection-Based Convolutional Neural Networks Optimized by Big Data
Choubineh, A., Chen, J., Coenen, F., & Ma, F. (2023). Applying Monte Carlo Dropout to Quantify the Uncertainty of Skip Connection-Based Convolutional Neural Networks Optimized by Big Data. ELECTRONICS, 12(6). doi:10.3390/electronics12061453
A Quantitative Insight Into the Role of Skip Connections in Deep Neural Networks of Low Complexity: A Case Study Directed at Fluid Flow Modeling
Choubineh, A., Chen, J., Coenen, F., & Ma, F. (2023). A Quantitative Insight Into the Role of Skip Connections in Deep Neural Networks of Low Complexity: A Case Study Directed at Fluid Flow Modeling. JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING, 23(1). doi:10.1115/1.4054868
Electrocardiogram Two-Dimensional Motifs: A Study Directed at Cardio Vascular Disease Classification
Aldosari, H., Coenen, F., Lip, G. Y. H., & Zheng, Y. (2023). Electrocardiogram Two-Dimensional Motifs: A Study Directed at Cardio Vascular Disease Classification. In Communications in Computer and Information Science (pp. 3-27). Springer Nature Switzerland. doi:10.1007/978-3-031-43471-6_1
Forecasting the UN Sustainable Development Goals
Alharbi, Y., Arribas-Bel, D., & Coenen, F. (2023). Forecasting the UN Sustainable Development Goals. In Communications in Computer and Information Science (pp. 88-110). Springer Nature Switzerland. doi:10.1007/978-3-031-37320-6_5
Fourier Neural Operator for Fluid Flow in Small-Shape 2D Simulated Porous Media Dataset
Choubineh, A., Chen, J., Wood, D. A., Coenen, F., & Ma, F. (2023). Fourier Neural Operator for Fluid Flow in Small-Shape 2D Simulated Porous Media Dataset. ALGORITHMS, 16(1). doi:10.3390/a16010024
PPNNBP: A Third Party Privacy-Preserving Neural Network With Back-Propagation Learning
Almutairi, N., Coenen, F., & Dures, K. (2023). PPNNBP: A Third Party Privacy-Preserving Neural Network With Back-Propagation Learning. IEEE ACCESS, 11, 31657-31675. doi:10.1109/ACCESS.2023.3263114
Preface
Coenen, F., Aveiro, D., Bernardino, J., Filipe, J., Fred, A., Dietz, J., & Masciari, E. (2023). Preface (Vol. 1842 CCIS).
2022
Query Resolution of Literature Knowledge Graphs using Hybrid Document Embeddings.
Coenen, F., Muhammad, I., Gamble, C., Kearney, A., & Williams, P. (2022). Query Resolution of Literature Knowledge Graphs using Hybrid Document Embeddings..
Scanned ECG Arrhythmia Classification Using a Pre-trained Convolutional Neural Network as a Feature Extractor
Coenen, F., Aldosari, H., Lip, G., & Zheng, Y. (2022). Scanned ECG Arrhythmia Classification Using a Pre-trained Convolutional Neural Network as a Feature Extractor.
From Deterministic to Stochastic: An Interpretable Stochastic Model-free Reinforcement Learning Framework for Portfolio Optimization
Coenen, F., Wang, Y., Song, Z., Qian, P., Song, S., Jiang, Z., & Su, J. (2022). From Deterministic to Stochastic: An Interpretable Stochastic Model-free Reinforcement Learning Framework for Portfolio Optimization. Applied Intelligence.
Retrieval-Based Language Model Adaptation for Handwritten Chinese Text Recognition
Coenen, F., Hu, S. -Y., Wang, Q. -F., Huang, K., & Wen, M. (2022). Retrieval-Based Language Model Adaptation for Handwritten Chinese Text Recognition. International Journal on Document Analysis and Recognition (IJDAR). doi:10.1007/s10032-022-00419-2
Geographic encoding of transcripts enabled high-accuracy and isoform-aware deep learning of RNA methylation
Huang, D., Chen, K., Song, B., Wei, Z., Su, J., Coenen, F., . . . Meng, J. (2022). Geographic encoding of transcripts enabled high-accuracy and isoform-aware deep learning of RNA methylation. NUCLEIC ACIDS RESEARCH, 50(18), 10290-10310. doi:10.1093/nar/gkac830
An innovative application of deep learning in multiscale modeling of subsurface fluid flow: Reconstructing the basis functions of the mixed GMsFEM
Choubineh, A., Chen, J., Coenen, F., & Ma, F. (2022). An innovative application of deep learning in multiscale modeling of subsurface fluid flow: Reconstructing the basis functions of the mixed GMsFEM. Journal of Petroleum Science and Engineering, 216, 110751. doi:10.1016/j.petrol.2022.110751
Zero-Shot Text Classification via Knowledge Graph Embedding for Social Media Data
Chen, Q., Wang, W., Huang, K., & Coenen, F. (2022). Zero-Shot Text Classification via Knowledge Graph Embedding for Social Media Data. IEEE INTERNET OF THINGS JOURNAL, 9(12), 9205-9213. doi:10.1109/JIOT.2021.3093065
BILATERAL-VIT FOR ROBUST FOVEA LOCALIZATION
Song, S., Dang, K., Yu, Q., Wang, Z., Coenen, F., Su, J., & Ding, X. (2022). BILATERAL-VIT FOR ROBUST FOVEA LOCALIZATION. In 2022 IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (IEEE ISBI 2022). doi:10.1109/ISBI52829.2022.9761523
A Robust Framework of Chromosome Straightening with ViT-Patch GAN
Advanced medical image classification with convolutional neural networks
Hu, H. (2022). Advanced medical image classification with convolutional neural networks.
Chapter Three Machine learning to improve natural gas reservoir simulations
Choubineh, A., Chen, J., Coenen, F., Ma, F., & Wood, D. A. (2022). Chapter Three Machine learning to improve natural gas reservoir simulations. In Sustainable Natural Gas Reservoir and Production Engineering (pp. 55-82). Elsevier. doi:10.1016/b978-0-12-824495-1.00011-5
Cross-Datasets Evaluation of Machine Learning Models for Intrusion Detection Systems
Al-Riyami, S., Lisitsa, A., & Coenen, F. (2022). Cross-Datasets Evaluation of Machine Learning Models for Intrusion Detection Systems. In Unknown Conference (pp. 815-828). Springer Singapore. doi:10.1007/978-981-16-2102-4_73
Data Augmentation for Pathology Prioritisation: An Improved LSTM-Based Approach
Qi, J., Burnside, G., & Coenen, F. (2022). Data Augmentation for Pathology Prioritisation: An Improved LSTM-Based Approach. In ARTIFICIAL INTELLIGENCE XXXIX, AI 2022 Vol. 13652 (pp. 51-63). doi:10.1007/978-3-031-21441-7_4
FOREWORD
Coenen, F., Fred, A., & Filipe, J. (2022). FOREWORD. In International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K - Proceedings Vol. 1 (pp. IX-X).
Pathology Data Prioritisation: A Study Using Multi-variate Time Series
Qi, J., Burnside, G., & Coenen, F. (2022). Pathology Data Prioritisation: A Study Using Multi-variate Time Series. In BIG DATA ANALYTICS AND KNOWLEDGE DISCOVERY, DAWAK 2022 Vol. 13428 (pp. 149-162). doi:10.1007/978-3-031-12670-3_13
Two-dimensional Motif Extraction from Images: A Study using an Electrocardiogram
Aldosari, H., Coenen, F., Lip, G., & Zheng, Y. (2022). Two-dimensional Motif Extraction from Images: A Study using an Electrocardiogram. In Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (pp. 19-28). SCITEPRESS - Science and Technology Publications. doi:10.5220/0011380500003335
2021
Finding banded patternsin large data set using segmentation
Abdullahi, F. B., & Coenen, F. (n.d.). Finding banded patternsin large data set using segmentation. Bayero Journal of Pure and Applied Sciences, 13(1), 90-96. doi:10.4314/bajopas.v13i1.13
Capturing Expert Knowledge for Building Enterprise SME Knowledge Graphs
Mansfield, M., Tamma, V., Goddard, P., & Coenen, F. (2021). Capturing Expert Knowledge for Building Enterprise SME Knowledge Graphs. In PROCEEDINGS OF THE 11TH KNOWLEDGE CAPTURE CONFERENCE (K-CAP '21) (pp. 129-136). doi:10.1145/3460210.3493569
A Novel Application of Image-to-Image Translation: Chromosome Straightening Framework by Learning from a Single Image
Song, S., Huang, D., Hu, Y., Yang, C., Meng, J., Ma, F., . . . Su, J. (2021). A Novel Application of Image-to-Image Translation: Chromosome Straightening Framework by Learning from a Single Image. In 2021 14TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, BIOMEDICAL ENGINEERING AND INFORMATICS (CISP-BMEI 2021). doi:10.1109/CISP-BMEI53629.2021.9624383
A survey on presentation attack detection for automatic speaker verification systems: State-of-the-art, taxonomy, issues and future direction
Tan, C. B., Hijazi, M. H. A., Khamis, N., Nohuddin, P. N. E. B., Zainol, Z., Coenen, F., & Gani, A. (n.d.). A survey on presentation attack detection for automatic speaker verification systems: State-of-the-art, taxonomy, issues and future direction. Multimedia Tools and Applications. doi:10.1007/s11042-021-11235-x
Multi-modal Generative Adversarial Networks for Traffic Event Detection in Smart Cities
Coenen, F., Wang, W., Chen, Q., Huang, K., & De, S. (2021). Multi-modal Generative Adversarial Networks for Traffic Event Detection in Smart Cities. Expert Systems With Applications. doi:10.1016/j.eswa.2021.114939
Sustainable Development Goal Relational Modelling and Prediction
Alharbi, Y., Arribas-Bel, D., & Coenen, F. (n.d.). Sustainable Development Goal Relational Modelling and Prediction. Journal of Data Intelligence, 2(3), 348-367. doi:10.26421/jdi2.3-3
Weakly supervised learning of RNA modifications from low-resolution epitranscriptome data
Huang, D., Song, B., Wei, J., Su, J., Coenen, F., & Meng, J. (2021). Weakly supervised learning of RNA modifications from low-resolution epitranscriptome data. In BIOINFORMATICS Vol. 37 (pp. I222-I230). doi:10.1093/bioinformatics/btab278
MetaTX: deciphering the distribution of mRNA-related features in the presence of isoform ambiguity, with applications in epitranscriptome analysis
Wang, Y., Chen, K., Wei, Z., Coenen, F., Su, J., & Meng, J. (2021). MetaTX: deciphering the distribution of mRNA-related features in the presence of isoform ambiguity, with applications in epitranscriptome analysis. BIOINFORMATICS, 37(9), 1285-1291. doi:10.1093/bioinformatics/btaa938
Automated Social Text Annotation With Joint Multilabel Attention Networks
Dong, H., Wang, W., Huang, K., & Coenen, F. (2021). Automated Social Text Annotation With Joint Multilabel Attention Networks. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 32(5), 2224-2238. doi:10.1109/TNNLS.2020.3002798
Efficient Distributed MST Based Clustering for Recommender System
Coenen, F., & Shahzad, A. (2021). Efficient Distributed MST Based Clustering for Recommender System. In IEEE International Conference on Data Minimg (ICDM) Workshop on Advanced Neural Algorithms and Theories for Recommender Systems (NeuRec).
Addressing the Challenge of Data Heterogeneity Using a Homogeneous Feature Vector Representation: A Study Using Time Series and Cardiovascular Disease Classification
Aldosari, H., Coenen, F., Lip, G. Y. H., & Zheng, Y. (2021). Addressing the Challenge of Data Heterogeneity Using a Homogeneous Feature Vector Representation: A Study Using Time Series and Cardiovascular Disease Classification. In ARTIFICIAL INTELLIGENCE XXXVIII Vol. 13101 (pp. 254-266). doi:10.1007/978-3-030-91100-3_21
Document Ranking for Curated Document Databases Using BERT and Knowledge Graph Embeddings: Introducing GRAB-Rank
Muhammad, I., Bollegala, D., Coenen, F., Gamble, C., Kearney, A., & Williamson, P. (2021). Document Ranking for Curated Document Databases Using BERT and Knowledge Graph Embeddings: Introducing GRAB-Rank. In BIG DATA ANALYTICS AND KNOWLEDGE DISCOVERY (DAWAK 2021) Vol. 12925 (pp. 116-127). doi:10.1007/978-3-030-86534-4_10
Event-based Pathology Data Prioritisation: A Study using Multi-variate Time Series Classification
Qi, J., Burnside, G., Charnley, P., & Coenen, F. (2021). Event-based Pathology Data Prioritisation: A Study using Multi-variate Time Series Classification. In PROCEEDINGS OF THE 13TH INTERNATIONAL JOINT CONFERENCE ON KNOWLEDGE DISCOVERY, KNOWLEDGE ENGINEERING AND KNOWLEDGE MANAGEMENT (KDIR), VOL 1: (pp. 121-128). doi:10.5220/0010643900003064
Machine learning to improve natural gas reservoir simulations
Choubineh, A., Chen, J., Coenen, F., Ma, F., & Wood, D. A. (2022). Machine learning to improve natural gas reservoir simulations. In Sustainable Natural Gas Reservoir and Production Engineering (pp. 55-82). Elsevier. doi:10.1016/b978-0-12-824495-1.00011-5
Management of non-urgent paediatric emergency department attendances by GPs: a retrospective observational study
Leigh, S., Mehta, B., Dummer, L., Aird, H., McSorley, S., Oseyenum, V., . . . Carrol, E. D. (2021). Management of non-urgent paediatric emergency department attendances by GPs: a retrospective observational study. BRITISH JOURNAL OF GENERAL PRACTICE, 71(702), E22-E30. doi:10.3399/bjgp20X713885
Motif Based Feature Vectors: Towards a Homogeneous Data Representation for Cardiovascular Diseases Classification
Aldosari, H., Coenen, F., Lip, G. Y. H., & Zheng, Y. (2021). Motif Based Feature Vectors: Towards a Homogeneous Data Representation for Cardiovascular Diseases Classification. In BIG DATA ANALYTICS AND KNOWLEDGE DISCOVERY (DAWAK 2021) Vol. 12925 (pp. 235-241). doi:10.1007/978-3-030-86534-4_22
Motif-based Classification using Enhanced Sub-Sequence-Based Dynamic Time Warping
Alshehri, M., Coenen, F., & Dures, K. (2021). Motif-based Classification using Enhanced Sub-Sequence-Based Dynamic Time Warping. In Proceedings of the 10th International Conference on Data Science, Technology and Applications (pp. 184-191). SCITEPRESS - Science and Technology Publications. doi:10.5220/0010519300002993
Motif-based Classification using Enhanced Sub-Sequence-Based Dynamic Time Warping
Alshehri, M., Coenen, F., & Dures, K. (2021). Motif-based Classification using Enhanced Sub-Sequence-Based Dynamic Time Warping. In PROCEEDINGS OF THE 10TH INTERNATIONAL CONFERENCE ON DATA SCIENCE, TECHNOLOGY AND APPLICATIONS (DATA) (pp. 184-191). doi:10.5220/0010519301840191
Phonocardiogram classification using motif discovery
Alhijailan, H. (2021). Phonocardiogram classification using motif discovery.
Ranking Pathology Data in the Absence of a Ground Truth
Qi, J., Burnside, G., & Coenen, F. (2021). Ranking Pathology Data in the Absence of a Ground Truth. In ARTIFICIAL INTELLIGENCE XXXVIII Vol. 13101 (pp. 209-223). doi:10.1007/978-3-030-91100-3_18
Sequential Association Rule Mining Revisited: A Study Directed at Relational Pattern Mining for Multi-morbidity
Vincent-Paulraj, A., Burnside, G., Coenen, F., Pirmohamed, M., & Walker, L. (2021). Sequential Association Rule Mining Revisited: A Study Directed at Relational Pattern Mining for Multi-morbidity. In ARTIFICIAL INTELLIGENCE XXXVIII Vol. 13101 (pp. 241-253). doi:10.1007/978-3-030-91100-3_20
Sustainable Development Goals Monitoring and Forecasting using Time Series Analysis
Alharbi, Y., Arribas-Bel, D., & Coenen, F. (2021). Sustainable Development Goals Monitoring and Forecasting using Time Series Analysis. In PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON DEEP LEARNING THEORY AND APPLICATIONS (DELTA) (pp. 123-131). doi:10.5220/0010546101230131
Sustainable Development Goals Monitoring and Forecasting using Time Series Analysis
Alharbi, Y., Arribas-Bel, D., & Coenen, F. (2021). Sustainable Development Goals Monitoring and Forecasting using Time Series Analysis. In Proceedings of the 2nd International Conference on Deep Learning Theory and Applications (pp. 123-131). SCITEPRESS - Science and Technology Publications. doi:10.5220/0010546100002996
2020
Candidates Reduction and Enhanced Sub-Sequence-Based Dynamic Time Warping: A Hybrid Approach
Alshehri, M., Coenen, F., & Dures, K. (2020). Candidates Reduction and Enhanced Sub-Sequence-Based Dynamic Time Warping: A Hybrid Approach. In Unknown Conference (pp. 273-285). Springer International Publishing. doi:10.1007/978-3-030-63799-6_21
Adversarial Domain Adaptation for Crisis Data Classification on Social Media
Chen, Q., Wang, W., Huang, K., De, S., & Coenen, F. (2020). Adversarial Domain Adaptation for Crisis Data Classification on Social Media. In 2020 International Conferences on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics) (pp. 282-287). IEEE. doi:10.1109/ithings-greencom-cpscom-smartdata-cybermatics50389.2020.00061
Census Estimation using Histogram Representation of 3D Surfaces: A Case Study Focusing on the Karak Region
El-Salhi, S., Al-Haj, S., & Coenen, F. (n.d.). Census Estimation using Histogram Representation of 3D Surfaces: A Case Study Focusing on the Karak Region. International Journal of Advanced Computer Science and Applications, 11(10). doi:10.14569/ijacsa.2020.0111087
Sustainable Development Goal Relational Modelling: Introducing the SDG-CAP Methodology
Coenen, F., Alharbi, Y., & Arribas-Bel, D. (2020). Sustainable Development Goal Relational Modelling: Introducing the SDG-CAP Methodology. In Lecture Notes in Computer Science Vol. 12393 (pp. 183-196). Bratislava, Slovakia: Springer Nature.
Multi-modal Adversarial Training for Crisis-related Data Classification on Social Media
Chen, Q., Wang, W., Huang, K., De, S., & Coenen, F. (2020). Multi-modal Adversarial Training for Crisis-related Data Classification on Social Media. In 2020 IEEE INTERNATIONAL CONFERENCE ON SMART COMPUTING (SMARTCOMP) (pp. 232-237). doi:10.1109/SMARTCOMP50058.2020.00051
What matters when managing childhood fever in the emergency department? A discrete-choice experiment comparing the preferences of parents and healthcare professionals in the UK
Leigh, S., Robinson, J., Yeung, S., Coenen, F., Carrol, E. D., & Niessen, L. W. (2020). What matters when managing childhood fever in the emergency department? A discrete-choice experiment comparing the preferences of parents and healthcare professionals in the UK. ARCHIVES OF DISEASE IN CHILDHOOD, 105(8), 765-771. doi:10.1136/archdischild-2019-318209
Sustainable Development Goal Relational Modelling: Introducing the SDG-RMF Methodology
Alharbi, Y., Coenen, F., & Arribas-Bel, D. (2020). Sustainable Development Goal Relational Modelling: Introducing the SDG-RMF Methodology. Retrieved from https://crcs.seas.harvard.edu/
Evaluating Co-reference Chains based Conversation History in Conversational Question Answering
Mandya, A. A., Bollegala, D., & Coenen, F. P. (2020). Evaluating Co-reference Chains based Conversation History in Conversational Question Answering. In L. -M. Nguyen, X. -H. Phan, K. Hasida, & S. Tojo (Eds.), Computational Linguistics (pp. 283-292). Singapore: Springer. doi:10.1007/978-981-15-6168-9_24
Secure Third Party Data Clustering Using SecureCL, Φ-Data and Multi-User Order Preserving Encryption
Coenen, F., & Nawal, A. (2020). Secure Third Party Data Clustering Using SecureCL, Φ-Data and Multi-User Order Preserving Encryption. Expert Systems.
<i>Do not let the history haunt you</i> - Mitigating Compounding Errors in Conversational Question Answering
Mandya, A., O'Neill, J., Bollegala, D., & Coenen, F. (2020). <i>Do not let the history haunt you</i> - Mitigating Compounding Errors in Conversational Question Answering. In PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION (LREC 2020) (pp. 2017-2025). Retrieved from https://www.webofscience.com/
Do not let the history haunt you -- Mitigating Compounding Errors in Conversational Question Answering
Contextualised Graph Attention for Improved Relation Extraction
Mandya, A., Bollegala, D., & Coenen, F. (2020). Contextualised Graph Attention for Improved Relation Extraction. Retrieved from http://arxiv.org/abs/2004.10624v1
Contextualised Graph Attention for Improved Relation Extraction
Knowledge Base Enrichment by Relation Learning from Social Tagging Data
Dong, H., Wang, W., Coenen, F., & Huang, K. (2020). Knowledge Base Enrichment by Relation Learning from Social Tagging Data. Information Sciences. doi:10.1016/j.ins.2020.04.002
Querrying Encrypted Data in Graph Databases
Coenen, F. P., Lisitsa, A., & Aburawi, N. N. (2020). Querrying Encrypted Data in Graph Databases.
Deep-Channel uses deep neural networks to detect single-molecule events from patch-clamp data
Celik, N., O’Brien, F., Brennan, S., Rainbow, R. D., Dart, C., Zheng, Y., . . . Barrett-Jolley, R. (2020). Deep-Channel uses deep neural networks to detect single-molecule events from patch-clamp data. Communications Biology, 3, 1-10. doi:10.1038/s42003-019-0729-3
Evaluating Co-reference Chains Based Conversation History in Conversational Question Answering
Mandya, A., Bollegala, D., & Coenen, F. (2020). Evaluating Co-reference Chains Based Conversation History in Conversational Question Answering. In Computational Linguistics (Vol. 1215, pp. 280-292). Springer Nature. doi:10.1007/978-981-15-6168-9_24
Experiments in non-personalized future blood glucose level prediction
Bevan, R., & Coenen, F. (2020). Experiments in non-personalized future blood glucose level prediction. In CEUR Workshop Proceedings Vol. 2675 (pp. 100-104).
From Semi-automated to Automated Methods of Ontology Learning from Twitter Data
Alajlan, S., Coenen, F., & Mandya, A. (2020). From Semi-automated to Automated Methods of Ontology Learning from Twitter Data. In Unknown Conference (pp. 213-236). Springer International Publishing. doi:10.1007/978-3-030-66196-0_10
Graph Convolution over Multiple Dependency Sub-graphs for Relation Extraction
Mandya, A., Bollegala, D., & Coenen, F. (2020). Graph Convolution over Multiple Dependency Sub-graphs for Relation Extraction. In Proceedings of the 28th International Conference on Computational Linguistics (pp. 6424-6435). International Committee on Computational Linguistics. doi:10.18653/v1/2020.coling-main.565
In-Bed Human Pose Classification Using Sparse Inertial Signals
Elnaggar, O., Coenen, F., & Paoletti, P. (2020). In-Bed Human Pose Classification Using Sparse Inertial Signals. In Lecture Notes in Computer Science (pp. 331-344). Springer International Publishing. doi:10.1007/978-3-030-63799-6_25
Maintaining Curated Document Databases Using a Learning to Rank Model: The ORRCA Experience
Muhammad, I., Bollegala, D., Coenen, F., Gamble, C., Kearney, A., & Williamson, P. (2020). Maintaining Curated Document Databases Using a Learning to Rank Model: The ORRCA Experience. In Unknown Conference (pp. 345-357). Springer International Publishing. doi:10.1007/978-3-030-63799-6_26
Open Information Extraction for Knowledge Graph Construction
Muhammad, I., Kearney, A., Gamble, C., Coenen, F., & Williamson, P. (2020). Open Information Extraction for Knowledge Graph Construction. In Unknown Conference (pp. 103-113). Springer International Publishing. doi:10.1007/978-3-030-59028-4_10
Secure Outsourced kNN Data Classification over Encrypted Data Using Secure Chain Distance Matrices
Almutairi, N., Coenen, F., & Dures, K. (2020). Secure Outsourced kNN Data Classification over Encrypted Data Using Secure Chain Distance Matrices. In Unknown Conference (pp. 3-24). Springer International Publishing. doi:10.1007/978-3-030-49559-6_1
2019
Combining Textual and Visual Information for Typed and Handwritten Text Separation in Legal Documents
Torrisi, A., Bevan, R., Atkinson, K., Bollegala, D., & Coenen, F. (2019). Combining Textual and Visual Information for Typed and Handwritten Text Separation in Legal Documents. In LEGAL KNOWLEDGE AND INFORMATION SYSTEMS (JURIX 2019) Vol. 322 (pp. 223-228). doi:10.3233/FAIA190329
Effective Sub-Sequence-Based Dynamic Time Warping
Coenen, F. P., Dures, K., & Alshehri, M. (2019). Effective Sub-Sequence-Based Dynamic Time Warping. In SGAI 2019: Artificial Intelligence XXXVI (pp. 293).
Deep-Channel uses deep neural networks to detect single-molecule events from patch-clamp data
Celik, N., O’Brien, F., Brennan, S., Rainbow, R., Dart, C., Zheng, Y., . . . Barrett-Jolley, R. (n.d.). Deep-Channel uses deep neural networks to detect single-molecule events from patch-clamp data. BioRxiv. doi:10.1101/767418
A Cryptographic Ensemble for Secure Third Party Data Analysis: Collaborative Data Clustering Without Data Owner Participation
Almutairi, S. T., Coenen, F. P., & Dures, K. (2019). A Cryptographic Ensemble for Secure Third Party Data Analysis: Collaborative Data Clustering Without Data Owner Participation. Knowledge and Data Engineering. doi:10.1016/j.datak.2019.101734
Automated Bundle Pagination Using Machine Learning
Torrisi, A., Bevan, R., Atkinson, K., Bollegala, D., & Coenen, F. (2019). Automated Bundle Pagination Using Machine Learning. In Proceedings of the Seventeenth International Conference on Artificial Intelligence and Law (pp. 244-248). ACM. doi:10.1145/3322640.3326726
The cost of diagnostic uncertainty: a prospective economic analysis of febrile children attending an NHS emergency department
Leigh, S., Grant, A., Murray, N., Faragher, B., Desai, H., Dolan, S., . . . Carrol, E. D. (2019). The cost of diagnostic uncertainty: a prospective economic analysis of febrile children attending an NHS emergency department. BMC Medicine, 17. doi:10.1186/s12916-019-1275-z
Modified framework for sarcasm detection and classification in sentiment analysis
Coenen, F. P., Suhaimin, M. S. M., Hijazi, M. H. A., & Alfred, R. (n.d.). Modified framework for sarcasm detection and classification in sentiment analysis. Indonesian Journal of Electrical Engineering and Computer Science. doi:10.11591/ijeecs.v13.i3.pp1175-1183
Particle swarm Optimized Density-based Clustering and Classification: Supervised and unsupervised learning approaches
Guan, C., Yuen, K. K. F., & Coenen, F. (2019). Particle swarm Optimized Density-based Clustering and Classification: Supervised and unsupervised learning approaches. Swarm and Evolutionary Computation, 44, 876-896. doi:10.1016/j.swevo.2018.09.008
A Dataset for Inter-Sentence Relation Extraction using Distant Supervision
Mandya, A., Bollegala, D., Coenen, F., & Atkinson, K. (2018). A Dataset for Inter-Sentence Relation Extraction using Distant Supervision. In PROCEEDINGS OF THE ELEVENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION (LREC 2018) (pp. 1559-1565). Retrieved from https://www.webofscience.com/
Behavioural Biometric Continuous User Authentication Using Multivariate Keystroke Streams in the Spectral Domain
Alshehri, A., Coenen, F., & Bollegala, D. (2019). Behavioural Biometric Continuous User Authentication Using Multivariate Keystroke Streams in the Spectral Domain. In Communications in Computer and Information Science (pp. 43-66). Springer International Publishing. doi:10.1007/978-3-030-15640-4_3
Deep learning for diabetic retinopathy diagnosis & analysis
Pratt, H. (2019). Deep learning for diabetic retinopathy diagnosis & analysis.
Effective Frequent Motif Discovery for Long Time Series Classification: A Study using Phonocardiogram
Alhijailan, H., & Coenen, F. (2019). Effective Frequent Motif Discovery for Long Time Series Classification: A Study using Phonocardiogram. In KDIR: PROCEEDINGS OF THE 11TH INTERNATIONAL JOINT CONFERENCE ON KNOWLEDGE DISCOVERY, KNOWLEDGE ENGINEERING AND KNOWLEDGE MANAGEMENT - VOL 1: KDIR (pp. 266-273). doi:10.5220/0008018902660273
Extracting supporting evidence from medical negligence claim texts
Bevany, R., Torrisiy, A., Bollegalay, D., Coeneny, F., & Atkinsony, K. (2019). Extracting supporting evidence from medical negligence claim texts. In CEUR Workshop Proceedings Vol. 2429 (pp. 50-54).
Feature visualisation of classification of diabetic retinopathy using a convolutional neural network
Pratt, H., Coenen, F., Harding, S. P., Broadbent, D. M., & Zheng, Y. (2019). Feature visualisation of classification of diabetic retinopathy using a convolutional neural network. In CEUR Workshop Proceedings Vol. 2429 (pp. 23-29).
Image Representation for Image Mining: A Study Focusing on Mining Satellite Images for Census Data Collection
Coenen, F., & Dittakan, K. (2019). Image Representation for Image Mining: A Study Focusing on Mining Satellite Images for Census Data Collection. In Communications in Computer and Information Science (pp. 3-27). Springer International Publishing. doi:10.1007/978-3-319-99701-8_1
Joint Multi-Label Attention Networks for Social Text Annotation
Dong, H., Wang, W., Huang, K., & Coenen, F. (2019). Joint Multi-Label Attention Networks for Social Text Annotation. In 2019 CONFERENCE OF THE NORTH AMERICAN CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS: HUMAN LANGUAGE TECHNOLOGIES (NAACL HLT 2019), VOL. 1 (pp. 1348-1354). Retrieved from https://www.webofscience.com/
Motif Discovery in Long Time Series: Classifying Phonocardiograms
Alhijailan, H., & Coenen, F. (2019). Motif Discovery in Long Time Series: Classifying Phonocardiograms. In ARTIFICIAL INTELLIGENCE XXXVI Vol. 11927 (pp. 198-212). doi:10.1007/978-3-030-34885-4_16
Ontology Learning from Twitter Data
Alajlan, S., Coenen, F., Konev, B., & Mandya, A. (2019). Ontology Learning from Twitter Data. In KEOD: PROCEEDINGS OF THE 11TH INTERNATIONAL JOINT CONFERENCE ON KNOWLEDGE DISCOVERY, KNOWLEDGE ENGINEERING AND KNOWLEDGE MANAGEMENT - VOL 2: KEOD (pp. 94-103). doi:10.5220/0008067600940103
Preface
Wiratunga, N., Coenen, F., & Sani, S. (2019). Preface. In CEUR Workshop Proceedings Vol. 2429 (pp. II).
Sub-Sequence-Based Dynamic Time Warping
Alshehri, M., Coenen, F., & Dures, K. (2019). Sub-Sequence-Based Dynamic Time Warping. In KDIR: PROCEEDINGS OF THE 11TH INTERNATIONAL JOINT CONFERENCE ON KNOWLEDGE DISCOVERY, KNOWLEDGE ENGINEERING AND KNOWLEDGE MANAGEMENT - VOL 1: KDIR (pp. 274-281). doi:10.5220/0008053402740281
Sustainable Development Goal Attainment Prediction: A Hierarchical Framework using Time Series Modelling
Alharbi, Y., Arribas-Be, D., & Coenen, F. (2019). Sustainable Development Goal Attainment Prediction: A Hierarchical Framework using Time Series Modelling. In KDIR: PROCEEDINGS OF THE 11TH INTERNATIONAL JOINT CONFERENCE ON KNOWLEDGE DISCOVERY, KNOWLEDGE ENGINEERING AND KNOWLEDGE MANAGEMENT - VOL 1: KDIR (pp. 297-304). doi:10.5220/0008067202970304
2018
Secure Third Party Data Clustering Using Φ Data: Multi-User Order Preserving Encryption and Super Secure Chain Distance Matrices
Coenen, F. P., Almutairi, N., & Dures, K. (2018). Secure Third Party Data Clustering Using Φ Data: Multi-User Order Preserving Encryption and Super Secure Chain Distance Matrices. In Springer. Cambridge: Springer Nature.
Combining Long Short Term Memory and Convolutional Neural Network for Cross-Sentence n-ary Relation Extraction
Mandya, A., Bollegala, D., Coenen, F., & Atkinson, K. (2018). Combining Long Short Term Memory and Convolutional Neural Network for Cross-Sentence n-ary Relation Extraction. Retrieved from http://arxiv.org/abs/1811.00845v1
Combining Long Short Term Memory and Convolutional Neural Network for Cross-Sentence n-ary Relation Extraction
Iterative Keystroke Continuous Authentication: A Time Series Based Approach
Alshehri, A., Coenen, F., & Bollegala, D. (2018). Iterative Keystroke Continuous Authentication: A Time Series Based Approach. KUNSTLICHE INTELLIGENZ, 32(4), 231-243. doi:10.1007/s13218-018-0526-z
POSTER: A Re-evaluation of Intrusion Detection Accuracy: an Alternative Evaluation Strategy
Al-Riyami, S., Coenen, F., & Lisitsa, A. (2018). POSTER: A Re-evaluation of Intrusion Detection Accuracy: an Alternative Evaluation Strategy. In PROCEEDINGS OF THE 2018 ACM SIGSAC CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY (CCS'18) (pp. 2195-2197). doi:10.1145/3243734.3278490
Multi-Dimensional Banded Pattern Mining
Abdullahi, F., & Coenen, F. (2018). Multi-Dimensional Banded Pattern Mining.
Segmenting sound waves to support Phonocardiogram analysis: the PCGseg Approach
Alhijaillan, H., Coenen, F., Dukes-McEwan, J., & Thiyalgalingam, J. (2018). Segmenting sound waves to support Phonocardiogram analysis: the PCGseg Approach. In Society for the study of artificial intelligence and simulation of behaviour (AISB). Liverpool.
A comparative study of pivot selection strategies for unsupervised cross-domain sentiment classification
Cui, X., Al-Bazzaz, N., Bollegala, D., & Coenen, F. (2018). A comparative study of pivot selection strategies for unsupervised cross-domain sentiment classification. KNOWLEDGE ENGINEERING REVIEW, 33. doi:10.1017/S0269888918000085
Attributes-oriented clothing description and retrieval with multi-task convolutional neural network
Xia, Y., Chen, B., Lu, W., Coenen, F., & Zhang, B. (2017). Attributes-oriented clothing description and retrieval with multi-task convolutional neural network. In 2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) (pp. 804-808). IEEE. doi:10.1109/fskd.2017.8393378
Multilingual and Skew License Plate Detection Based on Extremal Regions
Qian, R., Zhang, B., Coenen, F., & Yue, Y. (2017). Multilingual and Skew License Plate Detection Based on Extremal Regions. In 2017 13TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (ICNC-FSKD) (pp. 850-855). Retrieved from https://www.webofscience.com/
Automated Diagnosis of Fundus Camera Images for Diabetic Retinopathy for Treatment Referral
Coenen, F. P., Pratt, H., Zheng, Y., Harding, S., Williams, B., & Broadbent, D. (2018). Automated Diagnosis of Fundus Camera Images for Diabetic Retinopathy for Treatment Referral. European Journal of Ophthalmology.
Performance of Case-Based Reasoning Retrieval Using Classification Based on Associations versus Jcolibri and FreeCBR: A Further Validation Study
Aljuboori, A. S., Coenen, F., Nsaif, M., & Parsons, D. J. (2018). Performance of Case-Based Reasoning Retrieval Using Classification Based on Associations versus Jcolibri and FreeCBR: A Further Validation Study. In Journal of Physics: Conference Series Vol. 1003 (pp. 012130). IOP Publishing. doi:10.1088/1742-6596/1003/1/012130
Mechanism for Sarcasm Detection and Classification in Malay Social Media
Suhaimin, M. S. M., Hijazi, M. H. A., Alfred, R., & Coenen, F. (2018). Mechanism for Sarcasm Detection and Classification in Malay Social Media. Advanced Science Letters, 24(2), 1388-1392. doi:10.1166/asl.2018.10755
Automatic Detection and Distinction of Retinal Vessel Bifurcations and Crossings in Colour Fundus Photography
Pratt, H., Williams, B. M., Ku, J. Y., Vas, C., McCann, E., Al-Bander, B., . . . Zheng, Y. (2018). Automatic Detection and Distinction of Retinal Vessel Bifurcations and Crossings in Colour Fundus Photography. JOURNAL OF IMAGING, 4(1). doi:10.3390/jimaging4010004
Classifier-Based Pattern Selection Approach for Relation Instance Extraction
Mandya, A., Bollegala, D., Coenen, F., & Atkinson, K. (2018). Classifier-Based Pattern Selection Approach for Relation Instance Extraction. In COMPUTATIONAL LINGUISTICS AND INTELLIGENT TEXT PROCESSING (CICLING 2017), PT I Vol. 10761 (pp. 418-434). doi:10.1007/978-3-319-77113-7_33
Data Clustering using Homomorphic Encryption and Secure Chain Distance Matrices
Almutairi, N., Coenen, F., & Dures, K. (2018). Data Clustering using Homomorphic Encryption and Secure Chain Distance Matrices. In Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (pp. 41-50). SCITEPRESS - Science and Technology Publications. doi:10.5220/0006890800410050
Data Clustering using Homomorphic Encryption and Secure Chain Distance Matrices.
Almutairi, N., Coenen, F., & Dures, K. (2018). Data Clustering using Homomorphic Encryption and Secure Chain Distance Matrices.. In A. L. N. Fred, & J. Filipe (Eds.), KDIR (pp. 39-48). SciTePress. Retrieved from http://www.informatik.uni-trier.de/~ley/db/conf/ic3k/kdir2018.html
Efficient and Effective Case Reject-Accept Filtering: A Study Using Machine Learning
Coenen, F. P., Bevan, R., Torrisi, A., Atkinson, K., & Bollegala, D. (n.d.). Efficient and Effective Case Reject-Accept Filtering: A Study Using Machine Learning. In JURIX 2018.
Frame-Based Semantic Patterns for Relation Extraction
Mandya, A., Bollegala, D., Coenen, F., & Atkinson, K. (2018). Frame-Based Semantic Patterns for Relation Extraction. In COMPUTATIONAL LINGUISTICS, PACLING 2017 Vol. 781 (pp. 51-62). doi:10.1007/978-981-10-8438-6_5
Learning relations from social tagging data
Dong, H., Wang, W., & Coenen, F. (2018). Learning Relations from Social Tagging Data. In PRICAI 2018: TRENDS IN ARTIFICIAL INTELLIGENCE, PT I Vol. 11012 (pp. 29-41). doi:10.1007/978-3-319-97304-3_3
Location-aware convolutional neural networks based breast tumor detection
Huafeng Hu., Coenen, F., Fei Ma., Thiyagalingam, J., & Jionglong Su. (2018). Location-aware convolutional neural networks based breast tumor detection. In IET Doctoral Forum on Biomedical Engineering, Healthcare, Robotics and Artificial Intelligence 2018 (BRAIN 2018) (pp. 4 (7 pp.)). Institution of Engineering and Technology. doi:10.1049/cp.2018.1724
Querying Encrypted Graph Databases
Aburawi, N., Lisitsa, A., & Coenen, F. (2018). Querying Encrypted Graph Databases. In ICISSP: PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON INFORMATION SYSTEMS SECURITY AND PRIVACY (pp. 447-451). doi:10.5220/0006660004470451
Rules for inducing hierarchies from social tagging data
Dong, H., Wang, W., & Coenen, F. (2018). Rules for Inducing Hierarchies from Social Tagging Data. In TRANSFORMING DIGITAL WORLDS, ICONFERENCE 2018 Vol. 10766 (pp. 345-355). doi:10.1007/978-3-319-78105-1_38
Spectral Analysis of Keystroke Streams: Towards Effective Real-time Continuous User Authentication
Alshehri, A., Coenen, F., & Bollegala, D. (2018). Spectral Analysis of Keystroke Streams: Towards Effective Real-time Continuous User Authentication. In ICISSP: PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON INFORMATION SYSTEMS SECURITY AND PRIVACY (pp. 62-73). doi:10.5220/0006606100620073
Third Party Data Clustering Over Encrypted Data Without Data Owner Participation: Introducing the Encrypted Distance Matrix
Almutairi, N., Coenen, F., & Dures, K. (2018). Third Party Data Clustering Over Encrypted Data Without Data Owner Participation: Introducing the Encrypted Distance Matrix. In BIG DATA ANALYTICS AND KNOWLEDGE DISCOVERY (DAWAK 2018) Vol. 11031 (pp. 163-173). doi:10.1007/978-3-319-98539-8_13
Traversal-aware Encryption Adjustment for Graph Databases
Aburawi, N., Coenen, F., & Lisitsa, A. (2018). Traversal-aware Encryption Adjustment for Graph Databases. In Proceedings of the 7th International Conference on Data Science, Technology and Applications (pp. 381-387). SCITEPRESS - Science and Technology Publications. doi:10.5220/0006916403810387
2017
FCNNs: Fourier Convolutional Neural Networks
Pratt, H., Williams, B. M., Coenen, F. P., & Zheng, Y. (2017). FCNNs: Fourier Convolutional Neural Networks. In MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2017 Vol. 10534 (pp. 786-798). doi:10.1007/978-3-319-71249-9_47
TSP: Learning Task-Specific Pivots for Unsupervised Domain Adaptation
Coenen, F. P., Cui., & bollegala. (2017). TSP: Learning Task-Specific Pivots for Unsupervised Domain Adaptation. In ECML-PKDD.
Spectral Keyboard Streams: Towards Effective and Continuous Authentication
Coenen, F. P., alshehri., & bollegala. (2017). Spectral Keyboard Streams: Towards Effective and Continuous Authentication.
Mining the information architecture of the WWW using automated website boundary detection
Alshukri, A., & Coenen, F. (2017). Mining the information architecture of the WWW using automated website boundary detection. WEB INTELLIGENCE, 15(4), 269-290. doi:10.3233/WEB-170365
Natural language processing based features for sarcasm detection: An investigation using bilingual social media texts
Suhaimin, M. S. M., Hijazi, M. H. A., Alfred, R., & Coenen, F. (2017). Natural language processing based features for sarcasm detection: An investigation using bilingual social media texts. In 2017 8th International Conference on Information Technology (ICIT) (pp. 703-709). IEEE. doi:10.1109/icitech.2017.8079931
K-Means Clustering Using Homomorphic Encryption and an Updatable Distance Matrix: Secure Third Party Data Clustering with Limited Data Owner Interaction
Coenen, F. P., Almutairi., & Dures, K. (2017). K-Means Clustering Using Homomorphic Encryption and an Updatable Distance Matrix: Secure Third Party Data Clustering with Limited Data Owner Interaction. In 19th International Conference on Big Data Analytics and Knowledge Discovery. Lyon, France.
A Prediction Model Based Approach to Open Space Steganography Detection in HTML Webpages
Coenen, F. P., Sedeeq, I., & Lisitsa. (2017). A Prediction Model Based Approach to Open Space Steganography Detection in HTML Webpages.
A Directed Acyclic Graph (DAG) Ensemble Classification Model: An Alternative Architecture for Hierarchical Classification
Alshdaifat, E., Coenen, F., & Dures, K. (2017). A Directed Acyclic Graph (DAG) Ensemble Classification Model: An Alternative Architecture for Hierarchical Classification. INTERNATIONAL JOURNAL OF DATA WAREHOUSING AND MINING, 13(3), 73-90. doi:10.4018/IJDWM.2017070104
Automatic detection and identification of retinal vessel junctions in colour fundus photography
Pratt, H., Williams, B. M., Ku, J., Coenen, F., & Zheng, Y. (2017). Automatic detection and identification of retinal vessel junctions in colour fundus photography. In Medical Image Understanding and Analysis (MIUA). Edinburgh.
CLIEL
García-Constantino, M., Atkinson, K., Bollegala, D., Chapman, K., Coenen, F., Roberts, C., & Robson, K. (2017). CLIEL. In Proceedings of the 16th edition of the International Conference on Articial Intelligence and Law (pp. 79-87). ACM. doi:10.1145/3086512.3086520
Reputation System Aggregation and Ageing Factor Selection using Subjective Opinions Classification
Coenen, F. P., abdeglmageed., & lisitsa. (2017). Reputation System Aggregation and Ageing Factor Selection using Subjective Opinions Classification.
On The Mining and Usage of Movement Patterns in Large Traffic Networks
Al-Zeyadi, M., Coenen, F., & Lisitsa, A. (2017). On The Mining and Usage of Movement Patterns in Large Traffic Networks. In 2017 IEEE INTERNATIONAL CONFERENCE ON BIG DATA AND SMART COMPUTING (BIGCOMP) (pp. 135-142). Retrieved from https://www.webofscience.com/
Bias aware lexicon-based Sentiment Analysis of Malay dialect on social media data: A study on the Sabah Language
Hijazi, M. H. A., Libin, L., Alfred, R., & Coenen, F. (2016). Bias aware lexicon-based Sentiment Analysis of Malay dialect on social media data: A study on the Sabah Language. In 2016 2nd International Conference on Science in Information Technology (ICSITech) (pp. 356-361). IEEE. doi:10.1109/icsitech.2016.7852662
Clustering of Tweet Users Based on Optimal Sets
Coenen, F. P., Dutta, A., & Paul, A. (2017). Clustering of Tweet Users Based on Optimal Sets.
Algorithm for Finding Influential User: Based on User's Information Diffusion Region
Namtirtha, A., Gupta, S., Dutta, A., Dutta, B., & Coenen, F. (2016). Algorithm for Finding Influential User: Based on User's Information Diffusion Region. In PROCEEDINGS OF THE 2016 IEEE REGION 10 CONFERENCE (TENCON) (pp. 2734-2738). Retrieved from https://www.webofscience.com/
Accurate Continuous and Non-intrusive User Authentication with Multivariate Keystroke Streaming
Alshehri, A., Coenen, F., & Bollegala, D. (2017). Accurate Continuous and Non-intrusive User Authentication with Multivariate Keystroke Streaming. In Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (pp. 61-70). SCITEPRESS - Science and Technology Publications. doi:10.5220/0006497200610070
Attribute Permutation Steganography Detection using Attribute Position Changes Count
Sedeeq, I., Coenen, F., & Lisitsa, A. (2017). Attribute Permutation Steganography Detection using Attribute Position Changes Count. In ICISSP: PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON INFORMATION SYSTEMS SECURITY AND PRIVACY (pp. 95-100). doi:10.5220/0006166400950100
Effect of Data Imbalance on Unsupervised Domain Adaptation of Part-of-Speech Tagging and Pivot Selection Strategies.
Cui, X., Coenen, F., & Bollegala, D. (2017). Effect of Data Imbalance on Unsupervised Domain Adaptation of Part-of-Speech Tagging and Pivot Selection Strategies.. In LIDTA@PKDD/ECML Vol. 74 (pp. 103-115). PMLR. Retrieved from http://proceedings.mlr.press/v74/
Extracting Movement Patterns from Video Data to Drive Multi-Agent Based Simulations
Tufail, M., Coenen, F., & Mu, T. (2017). Extracting Movement Patterns from Video Data to Drive Multi-Agent Based Simulations. In Unknown Conference (pp. 128-140). Springer International Publishing. doi:10.1007/978-3-319-67477-3_7
User-to-User Recommendation using the Concept of Movement Patterns: A Study using a Dating Social Network
Al-Zeyadi, M., Coenen, F., & Lisitsa, A. (2017). User-to-User Recommendation using the Concept of Movement Patterns: A Study using a Dating Social Network. In Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (pp. 173-180). SCITEPRESS - Science and Technology Publications. doi:10.5220/0006494601730180
Volumetric image classification using homogeneous decomposition and dictionary learning: A study using retinal optical coherence tomography for detecting age-related macular degeneration
Albarrak, A., Coenen, F., & Zheng, Y. (2017). Volumetric image classification using homogeneous decomposition and dictionary learning: A study using retinal optical coherence tomography for detecting age-related macular degeneration. COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, 55, 113-123. doi:10.1016/j.compmedimag.2016.07.007
2016
Towards Keystroke Continuous Authentication Using Time Series Analytics
Alshehri, A., Coenen, F., & Bollegala, D. (2016). Towards Keystroke Continuous Authentication Using Time Series Analytics. In Unknown Conference (pp. 325-339). Springer International Publishing. doi:10.1007/978-3-319-47175-4_24
The application of social network mining to cattle movement analysis: introducing the predictive trend mining framework
Nohuddin, P., Coenen, F., & Christley, R. (2016). The application of social network mining to cattle movement analysis: introducing the predictive trend mining framework. Social Network Analysis and Mining, 6(1). doi:10.1007/s13278-016-0353-x
Face Occlusion Detection Using Deep Convolutional Neural Networks
Xia, Y., Zhang, B., & Coenen, F. (2016). Face Occlusion Detection Using Deep Convolutional Neural Networks. International Journal of Pattern Recognition and Artificial Intelligence, 30(09), 1660010. doi:10.1142/s0218001416600107
Road Surface Traffic Sign Detection with Hybrid Region Proposal and Fast R-CNN
Qian, R., Liu, Q., Yue, Y., Coenen, F., & Zhang, B. (2016). Road Surface Traffic Sign Detection with Hybrid Region Proposal and Fast R-CNN. In 2016 12TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (ICNC-FSKD) (pp. 555-559). Retrieved from https://www.webofscience.com/
Traffic Sign Recognition with Convolutional Neural Network Based on Max Pooling Positions
Qian, R., Yue, Y., Coenen, F., & Zhang, B. (2016). Traffic Sign Recognition with Convolutional Neural Network Based on Max Pooling Positions. In 2016 12TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (ICNC-FSKD) (pp. 578-582). Retrieved from https://www.webofscience.com/
Keyboard Usage Authentication using Multi-variant Time Series Analysis
Coenen, F. P., Alshehri., & Bollegala. (2016). Keyboard Usage Authentication using Multi-variant Time Series Analysis. In Springer LNCS. Porto, Portugal.
Traffic sign recognition using visual attribute learning and convolutional neural network
Qian, R. -Q., Yue, Y., Coenen, F., & Zhang, B. -L. (2016). Traffic sign recognition using visual attribute learning and convolutional neural network. In 2016 International Conference on Machine Learning and Cybernetics (ICMLC) (pp. 386-391). IEEE. doi:10.1109/icmlc.2016.7860932
Visual Attribute Classification Using Feature Selection and Convolutional Neural Network
Qian, R., Yue, Y., Coenen, F., & Zhang, B. (2016). Visual Attribute Classification Using Feature Selection and Convolutional Neural Network. In PROCEEDINGS OF 2016 IEEE 13TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING (ICSP 2016) (pp. 649-653). Retrieved from https://www.webofscience.com/
Multi Agent Based Simulation Using Movement Patterns Mined from Video Data
Tufail, M., Coenen, F., Hurst, J., & Mu, T. (2015). Multi Agent Based Simulation Using Movement Patterns Mined from Video Data. In Unknown Conference (pp. 275-287). Springer International Publishing. doi:10.1007/978-3-319-25032-8_21
Video-Based Classification of Driving Behavior Using a Hierarchical Classification System with Multiple Features
Yan, C., Coenen, F., Yue, Y., Yang, X., & Zhang, B. (2016). Video-Based Classification of Driving Behavior Using a Hierarchical Classification System with Multiple Features. INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 30(5). doi:10.1142/S0218001416500105
Mining frequent itemsets using the N-list and subsume concepts
Vo, B., Le, T., Coenen, F., & Hong, T. -P. (2016). Mining frequent itemsets using the N-list and subsume concepts. International Journal of Machine Learning and Cybernetics, 7(2), 253-265. doi:10.1007/s13042-014-0252-2
Banded Pattern Mining Algorithms in Multi-dimensional Zero-One Data
Abdullahi, F., Coenen, F. P., & Martin, R. (2016). Banded Pattern Mining Algorithms in Multi-dimensional Zero-One Data.
Driving posture recognition by convolutional neural networks
Yan, C., Coenen, F., & Zhang, B. (2016). Driving posture recognition by convolutional neural networks. IET COMPUTER VISION, 10(2), 103-114. doi:10.1049/iet-cvi.2015.0175
A Statistical Approach to The Detection of HTML Attribute Permutation.
Coenen, F. P., lisitsa., & sedeeq. (2016). A Statistical Approach to The Detection of HTML Attribute Permutation..
Multi-attributes Gait Identification by Convolutional Neural Networks
Yan, C., Zhang, B., & Coenen, F. (2015). Multi-attributes Gait Identification by Convolutional Neural Networks. In 2015 8TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING (CISP) (pp. 642-647). Retrieved from https://www.webofscience.com/
Recognizing Driver Inattention by Convolutional Neural Networks
Yan, C., Jiang, H., Zhang, B., & Coenen, F. (2015). Recognizing Driver Inattention by Convolutional Neural Networks. In 2015 8TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING (CISP) (pp. 680-685). Retrieved from https://www.webofscience.com/
Face occlusion detection based on multi-task convolution neural network
Yizhang Xia., Bailing Zhang., & Coenen, F. (2015). Face occlusion detection based on multi-task convolution neural network. In 2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) (pp. 375-379). IEEE. doi:10.1109/fskd.2015.7381971
Traffic Sign Detection by Template Matching based on Multi-Level Chain Code Histogram
Qian, R., Zhang, B., Yue, Y., & Coenen, F. (2015). Traffic Sign Detection by Template Matching based on Multi-Level Chain Code Histogram. In 2015 12TH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (FSKD) (pp. 2400-2404). Retrieved from https://www.webofscience.com/
Towards An Intuitionistic Fuzzy Agglomerative Hierarchical Clustering Algorithm for Music Recommendation in Folksonomy
Guan, C., Yuen, K. K. F., & Coenen, F. (2015). Towards An Intuitionistic Fuzzy Agglomerative Hierarchical Clustering Algorithm for Music Recommendation in Folksonomy. In 2015 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2015): BIG DATA ANALYTICS FOR HUMAN-CENTRIC SYSTEMS (pp. 2039-2042). doi:10.1109/SMC.2015.356
Driving posture recognition by convolutional neural networks
Chao Yan., Zhang, B., & Coenen, F. (2015). Driving posture recognition by convolutional neural networks. In 2015 11th International Conference on Natural Computation (ICNC) (pp. 680-685). IEEE. doi:10.1109/icnc.2015.7378072
Robust Chinese Traffic Sign Detection and Recognition with Deep Convolutional Neural Network
Qian, R., Zhang, B., Yue, Y., Wang, Z., & Coenen, F. (2015). Robust Chinese Traffic Sign Detection and Recognition with Deep Convolutional Neural Network. In 2015 11TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION (ICNC) (pp. 791-796). Retrieved from https://www.webofscience.com/
3-D Volume of Interest Based Image Classification
Udomchaiporn, A., Coenen, F., Garcia-Finana, M., & Sluming, V. (2016). 3-D Volume of Interest Based Image Classification. In PRICAI 2016: TRENDS IN ARTIFICIAL INTELLIGENCE Vol. 9810 (pp. 543-555). doi:10.1007/978-3-319-42911-3_45
A Statistical Approach to the Detection of HTML Attribute Permutation Steganography
Iman, S., Frans, C., & Alexei, L. (2016). A Statistical Approach to the Detection of HTML Attribute Permutation Steganography. In Proceedings of the 2nd International Conference on Information Systems Security and Privacy (pp. 522-527). SCITEPRESS - Science and and Technology Publications. doi:10.5220/0005801705220527
Banded Pattern Mining Algorithms in Multi-dimensional Zero-One Data
Abdullahi, F. B., Coenen, F., & Martin, R. (2016). Banded Pattern Mining Algorithms in Multi-dimensional Zero-One Data. In Unknown Conference (pp. 1-31). Springer Berlin Heidelberg. doi:10.1007/978-3-662-49784-5_1
Convolutional Neural Networks for Diabetic Retinopathy
Pratt, H., Coenen, F., Broadbent, D. M., Harding, S. P., & Zheng, Y. (2016, July 6). Convolutional Neural Networks for Diabetic Retinopathy. In Procedia Computer Science Vol. 90 (pp. 200-205). Loughbrough University: Elsevier. doi:10.1016/j.procs.2016.07.014
Early Detection of Osteoarthritis Using Local Binary Patterns: A Study Directed at Human Joint Imagery
Dittakan, K., & Coenen, F. (2016). Early Detection of Osteoarthritis Using Local Binary Patterns: A Study Directed at Human Joint Imagery. In Unknown Conference (pp. 93-105). Springer International Publishing. doi:10.1007/978-3-319-42911-3_8
Mining Frequent Movement Patterns in Large Networks: A Parallel Approach Using Shapes
Al-Zeyadi, M., Coenen, F., & Lisitsa, A. (2016). Mining Frequent Movement Patterns in Large Networks: A Parallel Approach Using Shapes. In Unknown Conference (pp. 53-67). Springer International Publishing. doi:10.1007/978-3-319-47175-4_4
nDrites: Enabling Laboratory Resource Multi-agent Systems
Atkinson, K., Coenen, F., Goddard, P., Payne, T. R., & Riley, L. (2016). nDrites: Enabling Laboratory Resource Multi-agent Systems. In ENGINEERING MULTI-AGENT SYSTEMS, EMAS 2016 Vol. 10093 (pp. 1-21). doi:10.1007/978-3-319-50983-9_1
2015
Finding Banded Patterns in Big Data Using Sampling
Abdullahi, F. B., Coenen, F., & Martin, R. (2015). Finding Banded Patterns in Big Data Using Sampling. In PROCEEDINGS 2015 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (pp. 2233-2242). Retrieved from https://www.webofscience.com/
Scalable Distributed Collaborative Tracking and Mapping with Micro Aerial Vehicles
Williams, R., Konev, B., & Coenen, F. (2015). Scalable Distributed Collaborative Tracking and Mapping with Micro Aerial Vehicles. In 2015 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) (pp. 3092-3097). Retrieved from https://www.webofscience.com/
Erratum to: One-class kernel subspace ensemble for medical image classification
Zhang, Y., Zhang, B., Coenen, F., Xiao, J., & Lu, W. (2015). Erratum to: One-class kernel subspace ensemble for medical image classification. EURASIP Journal on Advances in Signal Processing, 2015(1). doi:10.1186/s13634-015-0274-2
An intelligent process model: predicting springback in single point incremental forming
Khan, M. S., Coenen, F., Dixon, C., El-Salhi, S., Penalva, M., & Rivero, A. (2015). An intelligent process model: predicting springback in single point incremental forming. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 76(9-12), 2071-2082. doi:10.1007/s00170-014-6431-1
Classification of 3D Surface Data Using the Concept of Vertex Unique Labelled Subgraphs
Yu, W., Coenen, F., Zito, M., & Dittakan, K. (2014). Classification of 3D Surface Data Using the Concept of Vertex Unique Labelled Subgraphs. In 2014 IEEE International Conference on Data Mining Workshop (ICDMW) (pp. 47-54). doi:10.1109/ICDMW.2014.125
A Directed Acyclic Graph Based Approach to Multi-Class Ensemble Classification
Alshdaifat, E., Coenen, F., & Dures, K. (2015). A Directed Acyclic Graph Based Approach to Multi-Class Ensemble Classification. In Unknown Conference (pp. 43-57). Springer International Publishing. doi:10.1007/978-3-319-25032-8_3
Collaborating Low Cost Micro Aerial Vehicles: A Demonstration
Williams, R., Konev, B., & Coenen, F. (2015). Collaborating Low Cost Micro Aerial Vehicles: A Demonstration. TOWARDS AUTONOMOUS ROBOTIC SYSTEMS (TAROS 2015), 9287, 296-302. doi:10.1007/978-3-319-22416-9_33
Data Stream Mining with Limited Validation Opportunity: Towards Instrument Failure Prediction
Atkinson, K., Coenen, F., Goddard, P., Payne, T., & Riley, L. (2015). Data Stream Mining with Limited Validation Opportunity: Towards Instrument Failure Prediction. In BIG DATA ANALYTICS AND KNOWLEDGE DISCOVERY Vol. 9263 (pp. 283-295). doi:10.1007/978-3-319-22729-0_22
Finding Banded Patterns in Data: The Banded Pattern Mining Algorithm
Abdullahi, F. B., Coenen, F., & Martin, R. (2015). Finding Banded Patterns in Data: The Banded Pattern Mining Algorithm. In BIG DATA ANALYTICS AND KNOWLEDGE DISCOVERY Vol. 9263 (pp. 95-107). doi:10.1007/978-3-319-22729-0_8
Message from the workshop chairs
Yu, P. S., Cao, L., Zeng, Y., An, B., Symeonidis, A. L., Gorodetsky, V., & Coenen, F. (2015). Message from the workshop chairs. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) Vol. 9145 (pp. v-vi).
Mining Movement Patterns from Video Data to Inform Multi-agent Based Simulation
Tufail, M., Coenen, F., Mu, T., & Rind, S. J. (2015). Mining Movement Patterns from Video Data to Inform Multi-agent Based Simulation. In AGENTS AND DATA MINING INTERACTION (ADMI 2014) Vol. 9145 (pp. 38-51). doi:10.1007/978-3-319-20230-3_4
Predicting "springback" using 3D surface representation techniques: A case study in sheet metal forming
El Salhi, S., Coenen, F., Dixon, C., & Khan, M. S. (2015). Predicting "springback" using 3D surface representation techniques: A case study in sheet metal forming. EXPERT SYSTEMS WITH APPLICATIONS, 42(1), 79-93. doi:10.1016/j.eswa.2014.07.041
Visualisation of Trend Pattern Migrations in Social Networks
Nohuddin, P. N. E., Coenen, F., Christley, R., & Sunayama, W. (2015). Visualisation of Trend Pattern Migrations in Social Networks. In Unknown Conference (pp. 77-88). Springer International Publishing. doi:10.1007/978-3-319-25939-0_7
2014
One-class kernel subspace ensemble for medical image classification
Zhang, Y., Zhang, B., Coenen, F., Xiao, J., & Lu, W. (2014). One-class kernel subspace ensemble for medical image classification. EURASIP Journal on Advances in Signal Processing, 2014(1). doi:10.1186/1687-6180-2014-17
Age-related Macular Degeneration Screening using Data Mining Approaches
Hijazi, M. H. A., Coenen, F., & Zheng, Y. (2013). Age-related Macular Degeneration Screening using Data Mining Approaches. In 2013 FIRST INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, MODELLING AND SIMULATION (AIMS 2013) (pp. 299-303). doi:10.1109/AIMS.2013.55
Trend mining in social networks: from trend identification to visualization
Nohuddin, P. N. E., Sunayama, W., Christley, R., Coenen, F., & Setzkorn, C. (2014). Trend mining in social networks: from trend identification to visualization. EXPERT SYSTEMS, 31(5), 457-468. doi:10.1111/exsy.12024
A Dynamic Approach To The Website Boundary Detection Problem Using Random Walks
Alshukri, A., & Coenen, F. (2014). A Dynamic Approach To The Website Boundary Detection Problem Using Random Walks. In 2014 IEEE/WIC/ACM INTERNATIONAL JOINT CONFERENCES ON WEB INTELLIGENCE (WI) AND INTELLIGENT AGENT TECHNOLOGIES (IAT), VOL 2 (pp. 9-14). doi:10.1109/WI-IAT.2014.74
Cascading One-Class Kernel Subspace Ensembles for Reliable Biopsy Image Classification
Zhang, Y., Zhang, B., Coenen, F., & Lu, W. (2014). Cascading One-Class Kernel Subspace Ensembles for Reliable Biopsy Image Classification. Journal of Medical Imaging and Health Informatics, 4(2), 174-185. doi:10.1166/jmihi.2014.1238
Data mining for AMD screening: A classification based approach
Hijazi, M. H. A., Coenen, F., & Zheng, Y. (2014). Data mining for AMD screening: A classification based approach. International Journal of Simulation: Systems, Science and Technology, 15(2), 57-69. doi:10.5013/IJSSST.a.15.02.09
Driving Posture Recognition by Joint Application of Motion History Image and Pyramid Histogram of Oriented Gradients
Yan, C., Coenen, F., & Zhang, B. (2014). Driving Posture Recognition by Joint Application of Motion History Image and Pyramid Histogram of Oriented Gradients. International Journal of Vehicular Technology, 2014, 1-11. doi:10.1155/2014/719413
Driving Posture Recognition by Joint Application of Motion History Image and Pyramid histogram of Oriented Gradients
Yan, C., Coenen, F., & Zhang, B. (2014). Driving Posture Recognition by Joint Application of Motion History Image and Pyramid histogram of Oriented Gradients. In ADVANCES IN MECHATRONICS, AUTOMATION AND APPLIED INFORMATION TECHNOLOGIES, PTS 1 AND 2 Vol. 846-847 (pp. 1102-+). doi:10.4028/www.scientific.net/AMR.846-847.1102
Driving Posture Recognition by a Hierarchal Classification System with Multiple Features
Yan, C., Zhang, B., & Coenen, F. (2014). Driving Posture Recognition by a Hierarchal Classification System with Multiple Features. In 2014 7TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING (CISP 2014) (pp. 83-88). Retrieved from https://www.webofscience.com/
3-D MRI Brain Scan Classification Using A Point Series Based Representation
Udomchaiporn, A., Coenen, F., García-Fiñana, M., & Sluming, V. (2014). 3-D MRI Brain Scan Classification Using A Point Series Based Representation. Unknown Journal, 300-307. doi:10.1007/978-3-319-10160-6_27
3-D MRI Brain Scan Classification of Epilepsy Versus Non-epilepsy
Udomchaiporn, A., Coenen, F., GarcÃa-Fiñana, M., & Sluming, V. (2014). 3-D MRI Brain Scan Classification of Epilepsy Versus Non-epilepsy. In MIUA'14 (pp. 253-258). London: MIUA.
3D MRI Brain Scan Classification Using A Point Series Based Representation.
Udomchaiporn, A., Coenen, F., GarcÃa-Fiñana, M., & Sluming, V. (2014). 3D MRI Brain Scan Classification Using A Point Series Based Representation.. In DaWaK'14 (pp. 12 pages). Munich: Springer.
A Dynamic Approach To The Website Boundary Detection Problem Using Random Walks
Alshukri, A., & Coenen, F. (2014). A Dynamic Approach To The Website Boundary Detection Problem Using Random Walks. In WI'14 (pp. 12 pages). Warsaw: IEEE.
A Framework for Brand Reputation Mining and Visualisation
Alshukri, A., Coenen, F., Li, Y., Redfern, A., & Wong, P. W. H. (2014). A Framework for Brand Reputation Mining and Visualisation. In AI 2014 (pp. 12 pages). Cambridge, UK: Springer.
A Framework for Brand Reputation Mining and Visualisation
Alshukri, A., Coenen, F., Li, Y., Redfern, A., & Wong, P. W. H. (2014). A Framework for Brand Reputation Mining and Visualisation. In Unknown Conference (pp. 301-315). Springer International Publishing. doi:10.1007/978-3-319-12069-0_22
A Multi-Path Strategy for Hierarchical Ensemble Classification
Alshdaifat, E., Coenen, F., & Dures, K. (2014). A Multi-Path Strategy for Hierarchical Ensemble Classification. In MLDM'14 (pp. 12 pages). St Petersburg: Springer.
A Multi-path Strategy for Hierarchical Ensemble Classification
Alshdaifat, E., Coenen, F., & Dures, K. (2014). A Multi-path Strategy for Hierarchical Ensemble Classification. In MACHINE LEARNING AND DATA MINING IN PATTERN RECOGNITION, MLDM 2014 Vol. 8556 (pp. 198-212). Retrieved from https://www.webofscience.com/
A Novel Approach for Identifying Banded Patterns in Zero-One Data Using Column and Row Banding Scores
Abdullahi, F. B., Coenen, F., & Martin, R. (2014). A Novel Approach for Identifying Banded Patterns in Zero-One Data Using Column and Row Banding Scores. In MACHINE LEARNING AND DATA MINING IN PATTERN RECOGNITION, MLDM 2014 Vol. 8556 (pp. 58-72). Retrieved from https://www.webofscience.com/
A Scalable Algorithm for Banded Pattern Mining In Multi-Dimensional Zero-One Data
Abdullahi, F., Coenen, F., & Martin, R. (2014). A Scalable Algorithm for Banded Pattern Mining In Multi-Dimensional Zero-One Data. In DaWaK'14 (pp. 12 pages). Munich: Springer.
A Scalable Algorithm for Banded Pattern Mining in Multi-dimensional Zero-One Data
Abdullahi, F. B., Coenen, F., & Martin, R. (2014). A Scalable Algorithm for Banded Pattern Mining in Multi-dimensional Zero-One Data. In Unknown Conference (pp. 345-356). Springer International Publishing. doi:10.1007/978-3-319-10160-6_31
Content-Based Readability Assessment: A Study Using A Syllabic Alphabetic Language (Thai)
Tongtep, N., Coenen, F., & Theeramunkong, T. (2014). Content-Based Readability Assessment: A Study Using A Syllabic Alphabetic Language (Thai). In Lecture Notes in Computer Science (pp. 863-870). Springer International Publishing. doi:10.1007/978-3-319-13560-1_71
Dictionary Learning-Based Volumetric Image Classification for the Diagnosis of Age-Related Macular Degeneration
Albarrak, A., Coenen, F., & Zheng, Y. (2014). Dictionary Learning-Based Volumetric Image Classification for the Diagnosis of Age-Related Macular Degeneration. In MACHINE LEARNING AND DATA MINING IN PATTERN RECOGNITION, MLDM 2014 Vol. 8556 (pp. 272-284). Retrieved from https://www.webofscience.com/
Dictionary Learning-based Volumetric Image Classification for The Diagnosis of Age-related Macular Degeneration.
Albarrak, A., Coenen, F., & Zheng, Y. (2014). Dictionary Learning-based Volumetric Image Classification for The Diagnosis of Age-related Macular Degeneration.. In MLDM'14 (pp. 12 pages). St Petersburg: Springer.
Mining Movement Patterns from Video Data to Inform Multi Agent Based Simulation
Tufail, M., Coenen, F., & Mu, T. (2014). Mining Movement Patterns from Video Data to Inform Multi Agent Based Simulation. In ADMI'14 (pp. 12 pages). Paris: S[rimger.
Multi-agent Environment Exploration with AR.Drones
Williams, R., Konev, B., & Coenen, F. (2014). Multi-agent Environment Exploration with AR.Drones. In Unknown Conference (pp. 60-71). Springer International Publishing. doi:10.1007/978-3-319-10401-0_6
Multi-agent environment exploration with AR.Drones
Williams, R., Konev, B., & Coenen, F. (2014). Multi-agent environment exploration with AR.Drones. In TAROS'14 (pp. 12 pages). Birmingham: Springer.
Network Analysis of Parliamentary Debates: A Case Study on the UK House of Commons
Salah, Z., Coenen, F., & Grossi, D. (2014). Network Analysis of Parliamentary Debates: A Case Study on the UK House of Commons. In EUSN'14 (pp. 12 Pages). Barcelona: Springer.
Novel Approach for Identifying Banded Patterns In Zero-One Data Using Column and Row Banding Scores
Abdullahi, F., Coenen, F., & Martin, R. (2014). Novel Approach for Identifying Banded Patterns In Zero-One Data Using Column and Row Banding Scores. In MLDM'14 (pp. 12 pages). St Petersburg: Springer.
PRICAI 2014: Trends in Artificial Intelligence
Pham, D. -N., & Park, S. -B. (Eds.) (2014). PRICAI 2014: Trends in Artificial Intelligence. doi:10.1007/978-3-319-13560-1
2013
Classification of volumetric retinal images using overlapping decomposition and tree analysis
Albarrak, A., Coenen, F., & Zheng, Y. (2013). Classification of volumetric retinal images using overlapping decomposition and tree analysis. In Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems (pp. 11-16). IEEE. doi:10.1109/cbms.2013.6627757
3-D MRI Brain Scan Feature Classification Using an Oct-Tree Representation
Udomchaiporn, A., Coenen, F., García-Fiñana, M., & Sluming, V. (2013). 3-D MRI Brain Scan Feature Classification Using an Oct-Tree Representation. In Unknown Conference (pp. 229-240). Springer Berlin Heidelberg. doi:10.1007/978-3-642-53914-5_20
A Comparative Study of Three Image Representations for Population Estimation Mining Using Remote Sensing Imagery
Dittakan, K., Coenen, F., Christley, R., & Wardeh, M. (2013). A Comparative Study of Three Image Representations for Population Estimation Mining Using Remote Sensing Imagery. In Unknown Conference (pp. 253-264). Springer Berlin Heidelberg. doi:10.1007/978-3-642-53914-5_22
A Hybrid Approach for Mining Frequent Itemsets
Vo, B., Coenen, F., Le, T., & Hong, T. -P. (2013). A Hybrid Approach for Mining Frequent Itemsets. In 2013 IEEE International Conference on Systems, Man, and Cybernetics (pp. 4647-4651). IEEE. doi:10.1109/smc.2013.791
An Efficient Algorithm for Mining Erasable Itemsets Using the Difference of NC-Sets
Le, T., Vo, B., & Coenen, F. (2013). An Efficient Algorithm for Mining Erasable Itemsets Using the Difference of NC-Sets. In 2013 IEEE International Conference on Systems, Man, and Cybernetics (pp. 2270-2274). IEEE. doi:10.1109/smc.2013.388
Generating Domain-Specific Sentiment Lexicons for Opinion Mining
Salah, Z., Coenen, F., & Grossi, D. (2013). Generating Domain-Specific Sentiment Lexicons for Opinion Mining. In Unknown Conference (pp. 13-24). Springer Berlin Heidelberg. doi:10.1007/978-3-642-53914-5_2
Hierarchical Classification for Solving Multi-class Problems: A New Approach Using Naive Bayesian Classification
Alshdaifat, E., Coenen, F., & Dures, K. (2013). Hierarchical Classification for Solving Multi-class Problems: A New Approach Using Naive Bayesian Classification. In Unknown Conference (pp. 493-504). Springer Berlin Heidelberg. doi:10.1007/978-3-642-53914-5_42
Predicting Features in Complex 3D Surfaces Using a Point Series Representation: A Case Study in Sheet Metal Forming
El-Salhi, S., Coenen, F., Dixon, C., & Khan, M. S. (2013). Predicting Features in Complex 3D Surfaces Using a Point Series Representation: A Case Study in Sheet Metal Forming. In Unknown Conference (pp. 505-516). Springer Berlin Heidelberg. doi:10.1007/978-3-642-53914-5_43
Vertex Unique Labelled Subgraph Mining for Vertex Label Classification
Yu, W., Coenen, F., Zito, M., & El Salhi, S. (2013). Vertex Unique Labelled Subgraph Mining for Vertex Label Classification. In Unknown Conference (pp. 542-553). Springer Berlin Heidelberg. doi:10.1007/978-3-642-53914-5_46
Breast cancer diagnosis from biopsy images with highly reliable random subspace classifier ensembles
Zhang, Y., Zhang, B., Coenen, F., & Lu, W. (2013). Breast cancer diagnosis from biopsy images with highly reliable random subspace classifier ensembles. Machine Vision and Applications, 24(7), 1405-1420. doi:10.1007/s00138-012-0459-8
Minimal Vertex Unique Labelled Subgraph Mining
Yu, W., Coenen, F., Zito, M., & El Salhi, S. (2013). Minimal Vertex Unique Labelled Subgraph Mining. In Unknown Conference (pp. 317-326). Springer Berlin Heidelberg. doi:10.1007/978-3-642-40131-2_28
Population Estimation Mining Using Satellite Imagery
Dittakan, K., Coenen, F., Christley, R., & Wardeh, M. (2013). Population Estimation Mining Using Satellite Imagery. In Unknown Conference (pp. 285-296). Springer Berlin Heidelberg. doi:10.1007/978-3-642-40131-2_25
Feature Representation for Customer Attrition Risk Prediction in Retail Banking
Wang, Y. J., Di, G., Yu, J., Lei, J., & Coenen, F. (2013). Feature Representation for Customer Attrition Risk Prediction in Retail Banking. In Unknown Conference (pp. 229-238). Springer Berlin Heidelberg. doi:10.1007/978-3-642-39736-3_18
Satellite Image Mining for Census Collection: A Comparative Study with Respect to the Ethiopian Hinterland
Dittakan, K., Coenen, F., & Christley, R. (2013). Satellite Image Mining for Census Collection: A Comparative Study with Respect to the Ethiopian Hinterland. Unknown Journal, 260-274. doi:10.1007/978-3-642-39712-7_20
Extracting debate graphs from parliamentary transcripts
Salah, Z., Coenen, F., & Grossi, D. (2013). Extracting debate graphs from parliamentary transcripts. In Proceedings of the Fourteenth International Conference on Artificial Intelligence and Law (pp. 121-130). ACM. doi:10.1145/2514601.2514615
A new method for mining Frequent Weighted Itemsets based on WIT-trees
Vo, B., Coenen, F., & Le, B. (2013). A new method for mining Frequent Weighted Itemsets based on WIT-trees. Expert Systems with Applications, 40(4), 1256-1264. doi:10.1016/j.eswa.2012.08.065
A survey of frequent subgraph mining algorithms
Jiang, C., Coenen, F., & Zito, M. (2013). A survey of frequent subgraph mining algorithms. KNOWLEDGE ENGINEERING REVIEW, 28(1), 75-105. doi:10.1017/S0269888912000331
A Comparative Study of Three Image Representations for Population Estimation Mining Using Remote Sensing Imagery
Dittakan, K., Coenen, F., Christley, R., & Wardeh, M. (2013). A Comparative Study of Three Image Representations for Population Estimation Mining Using Remote Sensing Imagery. In ADMA'13 (pp. TBA). Hangzhou, China: Springer.
A Hybrid Approach for Mining Frequent Itemsets
Vo, B., Le, T., Coenen, F., & Hong, T. -P. (2013). A Hybrid Approach for Mining Frequent Itemsets. In SMC 2013 (pp. TBA). Manchester, UK.: IEEE.
A Multiagent Based Framework for the Simulation of Mammalian Behaviour
Agiriga, E., Coenen, F., Hurst, J., & Kowalsk, D. (2013). A Multiagent Based Framework for the Simulation of Mammalian Behaviour. In BCS-SGASI AI2013 (pp. TBA). Cambridge: Springer.
A Multiagent Based Framework for the Simulation of Mammalian Behaviour
Agiriga, E., Coenen, F., Hurst, J., & Kowalski, D. (2013). A Multiagent Based Framework for the Simulation of Mammalian Behaviour. In Research and Development in Intelligent Systems XXX (pp. 435-441). Springer International Publishing. doi:10.1007/978-3-319-02621-3_32
Age-related Macular Degeneration Identification In Volumetric Optical Coherence Tomography Using Decomposition and Local Feature Extraction
Albarrak, A., Coenen, F., & Zheng, Y. (2013). Age-related Macular Degeneration Identification In Volumetric Optical Coherence Tomography Using Decomposition and Local Feature Extraction. In MIUA (pp. 59-64). Birmingham: MIUA.
Age-related macular degeneration screening using data mining approaches.
Hijazi, M. H. A., Coenen, F., & Zheng, Y. (2013). Age-related macular degeneration screening using data mining approaches.. In 1st International Conference on Aritificial Intelligence, Modelling and Simulation (pp. 1-8). Kota Kinabalu: IEEE.
An Efficient Algorithm for Mining Erasable Itemsets Using the Difference of NC-Sets
Le, T., Vo, B., & Coenen, F. (2013). An Efficient Algorithm for Mining Erasable Itemsets Using the Difference of NC-Sets. In SMC'13 (pp. TBA). Manchester: IEEE.
An Inductive Rule Learning Technique for Text Mining in Questionnaires
Chua, S., & Coenen, F. (2013). An Inductive Rule Learning Technique for Text Mining in Questionnaires. In ICOCI 2013 (pp. TBA). Kuching, Sarawak, Malaysia: University Utara Malaysia.
Ben Valkenburg: a tribute
Beukema, L., & Coenen, F. (2013). Ben Valkenburg: a tribute. Transfer: European Review of Labour and Research, 19(2), 147-150. doi:10.1177/1024258913481295
Classification of Volumetric Retinal Images Using Overlapping Decomposition and Tree Analysis
Albarrak, A., Coenen, F., & Zheng, Y. (2013). Classification of Volumetric Retinal Images Using Overlapping Decomposition and Tree Analysis. In 2013 IEEE 26TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS) (pp. 11-16). Retrieved from https://www.webofscience.com/
Classification of Volumetric Retinal Images Using Overlapping Decomposition and Tree Analysis
Albarrak, A., Coenen, F., & Zheng, Y. (2013). Classification of Volumetric Retinal Images Using Overlapping Decomposition and Tree Analysis. In IEEE CBMS2013 (pp. 1-8). Porto: IEEE.
Classification of volumetric retinal images using overlapping decomposition and tree analysis
Albarrak, A., Coenen, F., & Zheng, Y. (2013). Classification of volumetric retinal images using overlapping decomposition and tree analysis. In The 26th IEEE International Symposium on Computer-Based Medical Systems (pp. 6). Porto, Portugal: IEEE.
Generating Domain-Specific Sentiment Lexicons for Opinion Mining
Salah, Z., Coenen, F., & Grossi, D. (2013). Generating Domain-Specific Sentiment Lexicons for Opinion Mining. In ADMA'13 (pp. TBA). Hangzhou, China: Soringer.
Hierarchical Classification for Solving Multi-class Problems: A New Approach Using Naive Bayesian Classification
Alshdaifat, E., Coenen, F., & Dures, K. (2013). Hierarchical Classification for Solving Multi-class Problems: A New Approach Using Naive Bayesian Classification. In ADMA'13 (pp. TBA). Hangzhou, China: Springer.
Hierarchical Single Label Classification: An Alternative Approach
Alshdaifat, E., Coenen, F., & Dures, K. (2013). Hierarchical Single Label Classification: An Alternative Approach. In Research and Development in Intelligent Systems XXX (pp. 39-52). Springer International Publishing. doi:10.1007/978-3-319-02621-3_3
Hierarchical Single Label classification: An Alternative Approach
Alshdaifat, E., Coenen, F., & Dures, K. (2013). Hierarchical Single Label classification: An Alternative Approach. In BCS-SGAI AI'2013 (pp. TBA). Cambridge, UK: Springer.
Predicting Features in Complex 3D Surfaces Using a Point Series Representation: A Case Study in Sheet Metal Forming
El Salhi, S., Coenen, F., Dixon, C., & Khan, M. (2013). Predicting Features in Complex 3D Surfaces Using a Point Series Representation: A Case Study in Sheet Metal Forming. In ADMA'13 (pp. TBA). Hangzhou, China: Springer.
Satellite Image Mining for Census Collection: A Comparative Study With Respect to the Ethiopian Hinterland
Dittakan, K., Coenen, F., & Christley, R. (2013). Satellite Image Mining for Census Collection: A Comparative Study With Respect to the Ethiopian Hinterland. In MLDM'13 (pp. 260-274). New York: Springer LNAI 7988.
Vertex Unique Labelled Subgraph Mining
Yu, W., Coenen, F., Zito, M., & Salhi, S. E. (2013). Vertex Unique Labelled Subgraph Mining. In Research and Development in Intelligent Systems XXX (pp. 21-37). Springer International Publishing. doi:10.1007/978-3-319-02621-3_2
Vertex Unique Labelled Subgraph Mining
Wen, Y., Coenen, F., Zito, M., & Salhi, S. (2013). Vertex Unique Labelled Subgraph Mining. In BCS-SGSI AI 20-13 (pp. TBA). Cambridge, UK: Springer.
Vertex Unique Labelled Subgraph Mining for Vertex Label Classification
Yu, W., Coenen, F., & Zito, M. (2013). Vertex Unique Labelled Subgraph Mining for Vertex Label Classification. In ADMA'13 (pp. TBA). Hangzhou, China: Springer.
2012
Automated "Disease/No Disease" Grading of Age-Related Macular Degeneration by an Image Mining Approach
Zheng, Y., Hijazi, M. H. A., & Coenen, F. (2012). Automated "Disease/No Disease" Grading of Age-Related Macular Degeneration by an Image Mining Approach. INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 53(13), 8310-8318. doi:10.1167/iovs.12-9576
An investigation into the issues of multi-agent data mining
Albashiri, K. A., Coenen, F., & Leng, P. (2012). An investigation into the issues of multi-agent data mining.
Volumetric Image Mining Based on Decomposition and Graph Analysis: An Application to Retinal Optical Coherence Tomography
Albarrak, A., Coenen, F., Zheng, Y., & Yu, W. (2012). Volumetric Image Mining Based on Decomposition and Graph Analysis: An Application to Retinal Optical Coherence Tomography. In 13TH IEEE INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND INFORMATICS (CINTI 2012) (pp. 263-268). Retrieved from https://www.webofscience.com/
A framework for Multi-Agent Based Clustering
Chaimontree, S., Atkinson, K., & Coenen, F. (2012). A framework for Multi-Agent Based Clustering. Autonomous Agents and Multi-Agent Systems, 25(3), 425-446. doi:10.1007/s10458-011-9187-0
Multi-agent based classification using argumentation from experience
Wardeh, M., Coenen, F., & Bench-Capon, T. (2012). Multi-agent based classification using argumentation from experience. AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS, 25(3), 447-474. doi:10.1007/s10458-012-9197-6
Identification and Visualisation of Pattern Migrations in Big Network Data
Nohuddin, P. N. E., Coenen, F., Christley, R., & Sunayama, W. (2012). Identification and Visualisation of Pattern Migrations in Big Network Data. In Unknown Conference (pp. 883-886). Springer Berlin Heidelberg. doi:10.1007/978-3-642-32695-0_91
Region Of Interest Based Image Classification: A Study in MRI Brain Scan Categorization
Elsayed, A., Coenen, F., Garca-Fiana, M., & Sluming, V. (n.d.). Region Of Interest Based Image Classification: A Study in MRI Brain Scan Categorization. In Data Mining Applications in Engineering and Medicine. InTech. doi:10.5772/50019
Highly reliable breast cancer diagnosis with cascaded ensemble classifiers
Yungang Zhang., Bailing Zhang., Coenenz, F., & Wenjin Lu. (2012). Highly reliable breast cancer diagnosis with cascaded ensemble classifiers. In The 2012 International Joint Conference on Neural Networks (IJCNN) (pp. 1-8). IEEE. doi:10.1109/ijcnn.2012.6252547
A Semi-Automated Approach to Building Text Summarisation Classifiers
Garcia-Constantino, M., Coenen, F., Noble, P. -J., Radford, A., & Setzkorn, C. (2012). A Semi-Automated Approach to Building Text Summarisation Classifiers. In Unknown Conference (pp. 495-509). Springer Berlin Heidelberg. doi:10.1007/978-3-642-31537-4_39
Finding Correlations between 3-D Surfaces: A Study in Asymmetric Incremental Sheet Forming
Khan, M. S., Coenen, F., Dixon, C., & El-Salhi, S. (2012). Finding Correlations between 3-D Surfaces: A Study in Asymmetric Incremental Sheet Forming. In Unknown Conference (pp. 366-379). Springer Berlin Heidelberg. doi:10.1007/978-3-642-31537-4_29
Data mining techniques for the screening of age-related macular degeneration
Hijazi, M. H. A., Coenen, F., & Zheng, Y. (2012). Data mining techniques for the screening of age-related macular degeneration. KNOWLEDGE-BASED SYSTEMS, 29, 83-92. doi:10.1016/j.knosys.2011.07.002
Finding "interesting" trends in social networks using frequent pattern mining and self organizing maps
Nohuddin, P. N. E., Coenen, F., Christley, R., Setzkorn, C., Patel, Y., & Williams, S. (2012). Finding "interesting" trends in social networks using frequent pattern mining and self organizing maps. KNOWLEDGE-BASED SYSTEMS, 29, 104-113. doi:10.1016/j.knosys.2011.07.003
Finding “interesting” trends in social networks using frequent pattern mining and self organizing maps
Nohuddin, P. N. E., Coenen, F., Christley, R., Setzkorn, C., Patel, Y., & Williams, S. (2012). Finding “interesting” trends in social networks using frequent pattern mining and self organizing maps. Knowledge-Based Systems, 29, 104-113. doi:10.1016/j.knosys.2011.07.003
PISA: A framework for multiagent classification using argumentation
Wardeh, M., Coenen, F., & Capon, T. B. (2012). PISA: A framework for multiagent classification using argumentation. DATA & KNOWLEDGE ENGINEERING, 75, 34-57. doi:10.1016/j.datak.2012.03.001
A Multi-agent Based Approach to Clustering: Harnessing the Power of Agents
Chaimontree, S., Atkinson, K., & Coenen, F. (2012). A Multi-agent Based Approach to Clustering: Harnessing the Power of Agents. In Unknown Conference (pp. 16-29). Springer Berlin Heidelberg. doi:10.1007/978-3-642-27609-5_3
A Semi-Automated Approach to Building Text Summarisation Classifiers
Garcia-Constantino, M., Coenen, F., Noble, P. -J., & Radford, A. (2012). A Semi-Automated Approach to Building Text Summarisation Classifiers. Journal of Theoretical and Applied Computer Science.
Classification Based 3-D Surface Analysis: Predicting Springback in Sheet Metal Forming
Khan, M. S., Coenen, F., Dixon, C., & El-Salhi, S. (2012). Classification Based 3-D Surface Analysis: Predicting Springback in Sheet Metal Forming. Journal of Theoretical and Applied Computer Science, 6(2), 45-59.
Identification of Correlations Between 3D Surfaces Using Data Mining Techniques: Predicting Springback in Sheet Metal Forming
El-Salhi, S., Coenen, F., Dixon, C., & Khan, M. S. (2012). Identification of Correlations Between 3D Surfaces Using Data Mining Techniques: Predicting Springback in Sheet Metal Forming. In Unknown Conference (pp. 391-404). Springer London. doi:10.1007/978-1-4471-4739-8_30
Image Mining Approaches for The Screening of Age-Related Macular Degeneration
Hijazi, M. H. A., Coenen, F., & Zheng, Y. (2012). Image Mining Approaches for The Screening of Age-Related Macular Degeneration. In Data Mining (Working Title) (pp. TBA). Hauppauge (NY), USA: Nova Sciences Publishers Inc..
Image mining approaches for the screening of age-related macular degeneration
Hijazi, M. H. A., Coenen, F., & Zheng, Y. (2012). Image mining approaches for the screening of age-related macular degeneration. In Retinopathy: New Research (pp. 101-142).
Questionnaire Free Text Summarisation Using Hierarchical Classification
Garcia-Constantino, M., Coenen, F., Noble, P. -J., & Radford, A. (2012). Questionnaire Free Text Summarisation Using Hierarchical Classification. In Unknown Conference (pp. 35-48). Springer London. doi:10.1007/978-1-4471-4739-8_3
Towards The Collection of Census Data From Satellite Imagery Using Data Mining: A Study With Respect to the Ethiopian Hinterland
Dittakan, K., Coenen, F., & Christley, R. (2012). Towards The Collection of Census Data From Satellite Imagery Using Data Mining: A Study With Respect to the Ethiopian Hinterland. In Unknown Conference (pp. 405-418). Springer London. doi:10.1007/978-1-4471-4739-8_31
2011
Time Series Case Based Reasoning for Image Categorisation
Elsayed, A., Hijazi, M. H. A., Coenen, F., Garcia-Finana, M., Sluming, V., & Zheng, Y. (2011). Time Series Case Based Reasoning for Image Categorisation. In CASE-BASED REASONING RESEARCH AND DEVELOPMENT, ICCBR 2011 Vol. 6880 (pp. 423-+). Retrieved from https://www.webofscience.com/
Image Classification for Age-related Macular Degeneration Screening Using Hierarchical Image Decompositions and Graph Mining
Hijazi, M. H. A., Jiang, C., Coenen, F., & Zheng, Y. (2011). Image Classification for Age-related Macular Degeneration Screening Using Hierarchical Image Decompositions and Graph Mining. In MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, PT II Vol. 6912 (pp. 65-80). Retrieved from https://www.webofscience.com/
An Investigation Concerning the Generation of Text Summarisation Classifiers Using Secondary Data
Garcia-Constantino, M., Coenen, F., Noble, P. -J., Radford, A., Setzkorn, C., & Tierney, A. (2011). An Investigation Concerning the Generation of Text Summarisation Classifiers Using Secondary Data. In Unknown Conference (pp. 387-398). Springer Berlin Heidelberg. doi:10.1007/978-3-642-23199-5_29
Incremental Web-Site Boundary Detection Using Random Walks
Alshukri, A., Coenen, F., & Zito, M. (2011). Incremental Web-Site Boundary Detection Using Random Walks. In Unknown Conference (pp. 414-427). Springer Berlin Heidelberg. doi:10.1007/978-3-642-23199-5_31
Finding Associations in Composite Data Sets
Khan, M. S., Muyeba, M., Coenen, F., Reid, D., & Tawfik, H. (2011). Finding Associations in Composite Data Sets. International Journal of Data Warehousing and Mining, 7(3), 1-29. doi:10.4018/jdwm.2011070101
Arguing from experience using multiple groups of agents
Wardeh, M., Bench-Capon, T., & Coenen, F. (2011). Arguing from experience using multiple groups of agents. Argument & Computation, 2(1), 51-76. doi:10.1080/19462166.2010.528176
Data mining: past, present and future
Coenen, F. (n.d.). Data mining: past, present and future. The Knowledge Engineering Review, 26(1), 25-29. doi:10.1017/s0269888910000378
A Comparative Study of Using CARM Approaches in Mesenchymal Stem Cell Differentiation Analysis
Wang, W., Wang, Y., Bañares-Alcántara, R., Cui, Z., & Coenen, F. P. (2011). A Comparative Study of Using CARM Approaches in Mesenchymal Stem Cell Differentiation Analysis. In A. V. Kumar Senthil (Ed.), Knowledge Discovery Practices and Emerging Applications of Data Mining: Trends and New Domains (pp. 223-243). Hershey (PA), USA: IGI Global.
A multi-agent based approach to clustering: Harnessing the power of agents
Chaimontree, S., Atkinson, K., & Coenen, F. (2011). A multi-agent based approach to clustering: Harnessing the power of agents. In Seventh International Workshop on Agents and Data Mining Interaction (pp. 103-114). Taiwan: Springer LNCS 5980.
Automated grading of age-related macular degeneration by an image mining approach
Zheng, Y., Hijazi, M. H. A., & Coenen, F. (2011). Automated grading of age-related macular degeneration by an image mining approach. In Inv Ophth Vis Sci Vol. 52 (pp. 6568).
Classification of MRI Brain Scan Data Using Shape Criteria
Elsayed, A., Hijazi, M. H. A., Coenen, F., Garcia-Finana, M., Sluming, V., & Zheng, Y. (2011). Classification of MRI Brain Scan Data Using Shape Criteria. Annals of the British Machine Vision Association (BMVA), 2011(6), 1-14. Retrieved from http://www.bmva.org/annals/2011/2011-0006.pdf
Finding Associations in Composite Data Sets: The CFARM Algorithm
Khan, M. S., Muyeba, M. K., Coenen, F., Reid, D., & Tawfik, H. (2011). Finding Associations in Composite Data Sets: The CFARM Algorithm. Journal of Data Warehousing and Mining, 7(31), 1-29.
Identifying Age-related Macular Degeneration In Volumetric Retinal Images.
Albarrak, A., Coenen, F., & Zheng, Y. (2011). Identifying Age-related Macular Degeneration In Volumetric Retinal Images.. In Ophthalmic Image Analysis Workshop (pp. 53-58). Liverpool: University of Liverpool.
Multi-agent Based Classification Using Argumentation from Experience
Wardeh, M., Coenen, F., Bench-Capon, T., & Wyner, A. (2011). Multi-agent Based Classification Using Argumentation from Experience. In ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PT II Vol. 6635 (pp. 357-369). Retrieved from https://www.webofscience.com/
Region of interest based image classification : a study in MRI brain scan categorization
Elsayed, A. S. A. (2011). Region of interest based image classification : a study in MRI brain scan categorization. doi:10.17638/03062822
Retinal Image Classification for the Screening of Age-Related Macular Degeneration
Hijazi, M. H. A., Coenen, F., & Zheng, Y. (2011). Retinal Image Classification for the Screening of Age-Related Macular Degeneration. In RESEARCH AND DEVELOPMENT IN INTELLIGENT SYSTEMS XXVII: INCORPORATING APPLICATIONS AND INNOVATIONS IN INTELLIGENT SYSTEMS XVIII (pp. 325-338). doi:10.1007/978-0-85729-130-1_25
Retinal image classification for the screening of age-related macular degeneration
Hijazi, M. H. A., Coenen, F., & Zheng, Y. (2011). Retinal image classification for the screening of age-related macular degeneration. In Res. and Dev. in Intelligent Syst. XXVII: Incorporating Applications and Innovations in Intel. Sys. XVIII - AI 2010, 30th SGAI Int. Conf. on Innovative Techniques and Applications of Artificial Intel. (pp. 325-338). doi:10.1007/978-0-85729-130-1_25
Rule Learning with Negation for Text Classification
Chua, S., Coenen, F., & Malcom, G. (2011). Rule Learning with Negation for Text Classification. In MLDM 2011 poster proceedings (pp. 1-14). New York: ibai-publisging.
SOMA: A Proposed Framework for Trend Mining in Large UK Diabetic Retinopathy Temporal Databases
Somaraki, V., Harding, S., Broadbent, D., & Coenen, F. (2011). SOMA: A Proposed Framework for Trend Mining in Large UK Diabetic Retinopathy Temporal Databases. In RESEARCH AND DEVELOPMENT IN INTELLIGENT SYSTEMS XXVII: INCORPORATING APPLICATIONS AND INNOVATIONS IN INTELLIGENT SYSTEMS XVIII (pp. 285-290). doi:10.1007/978-0-85729-130-1_22
SOMA: A proposed framework for trend mining in large UK diabetic retinopathy temporal databases
Somaraki, V., Harding, S., Broadbent, D., & Coenen, F. (2011). SOMA: A proposed framework for trend mining in large UK diabetic retinopathy temporal databases. In Res. and Dev. in Intelligent Syst. XXVII: Incorporating Applications and Innovations in Intel. Sys. XVIII - AI 2010, 30th SGAI Int. Conf. on Innovative Techniques and Applications of Artificial Intel. (pp. 285-290). doi:10.1007/978-0-85729-130-1_22
Social Network Trend Analysis Using Frequent Pattern Mining and Self Organizing Maps
Nohuddin, P. N. E., Christley, R., Coenen, F., Patel, Y., Setzkorn, C., & Williams, S. (2011). Social Network Trend Analysis Using Frequent Pattern Mining and Self Organizing Maps. In RESEARCH AND DEVELOPMENT IN INTELLIGENT SYSTEMS XXVII: INCORPORATING APPLICATIONS AND INNOVATIONS IN INTELLIGENT SYSTEMS XVIII (pp. 311-324). doi:10.1007/978-0-85729-130-1_24
Social network trend analysis using frequent pattern mining and self organizing maps
Nohuddin, P. N. E., Christley, R., Coenen, F., Patel, Y., Setzkorn, C., & Williams, S. (2011). Social network trend analysis using frequent pattern mining and self organizing maps. In Res. and Dev. in Intelligent Syst. XXVII: Incorporating Applications and Innovations in Intel. Sys. XVIII - AI 2010, 30th SGAI Int. Conf. on Innovative Techniques and Applications of Artificial Intel. (pp. 311-324). doi:10.1007/978-0-85729-130-1_24
The Application of AI Techniques to Deformation in Metal Manufacturing
Dixon, C., Coenen, F., & Khan, M. (2011). The Application of AI Techniques to Deformation in Metal Manufacturing. In WAR (pp. 17-18). Glasgow: University of Glasgow.
Towards Large-Scale Multi-Agent Based Rodent Simulation: The "Mice In A Box" Scenario
Agiriga, E., Coenen, F., Hurst, J., Beynon, R., & Kowalski, D. (2011). Towards Large-Scale Multi-Agent Based Rodent Simulation: The "Mice In A Box" Scenario. In RESEARCH AND DEVELOPMENT IN INTELLIGENT SYSTEMS XXVIII: INCORPORATING APPLICATIONS AND INNOVATIONS IN INTELLIGENT SYSTEMS XIX (pp. 369-+). doi:10.1007/978-1-4471-2318-7_28
Towards large-scale multi-agent based rodent simulation: The "mice in a box" scenario
Agiriga, E., Coenen, F., Hurst, J., Beynon, R., & Kowalski, D. (2011). Towards large-scale multi-agent based rodent simulation: The "mice in a box" scenario. In Res. and Dev. in Intelligent Syst. XXVIII: Incorporating Applications and Innovations in Intel. Sys. XIX - AI 2011, 31st SGAI Int. Conf. on Innovative Techniques and Applications of Artificial Intel. (pp. 369-382). doi:10.1007/978-1-4471-2318-7_28
Trend Mining and Visualisation in Social Networks
Nohuddin, P. N. E., Sunayama, W., Christley, R., Coenen, F., & Setzkorn, C. (2011). Trend Mining and Visualisation in Social Networks. In RESEARCH AND DEVELOPMENT IN INTELLIGENT SYSTEMS XXVIII: INCORPORATING APPLICATIONS AND INNOVATIONS IN INTELLIGENT SYSTEMS XIX (pp. 269-+). doi:10.1007/978-1-4471-2318-7_21
Trend mining and visualisation in social networks
Nohuddin, P. N. E., Sunayama, W., Christley, R., Coenen, F., & Setzkorn, C. (2011). Trend mining and visualisation in social networks. In Res. and Dev. in Intelligent Syst. XXVIII: Incorporating Applications and Innovations in Intel. Sys. XIX - AI 2011, 31st SGAI Int. Conf. on Innovative Techniques and Applications of Artificial Intel. (pp. 269-282). doi:10.1007/978-1-4471-2318-7_21
Using Negation and Phrases in Inducing Rules for Text Classification
Chua, S., Coenen, F., Malcolm, G., Fernando, M., & Constantino, G. (2011). Using Negation and Phrases in Inducing Rules for Text Classification. In Unknown Conference (pp. 153-166). Springer London. doi:10.1007/978-1-4471-2318-7_11
Web-Site Boundary Detection Using Incremental Random Walk Clustering
Alshukri, A., Coenen, F., & Zito, M. (2011). Web-Site Boundary Detection Using Incremental Random Walk Clustering. In RESEARCH AND DEVELOPMENT IN INTELLIGENT SYSTEMS XXVIII: INCORPORATING APPLICATIONS AND INNOVATIONS IN INTELLIGENT SYSTEMS XIX (pp. 255-268). doi:10.1007/978-1-4471-2318-7_20
Web-site boundary detection using incremental randomwalk clustering
Alshukri, A., Coenen, F., & Zito, M. (2011). Web-site boundary detection using incremental randomwalk clustering. In Res. and Dev. in Intelligent Syst. XXVIII: Incorporating Applications and Innovations in Intel. Sys. XIX - AI 2011, 31st SGAI Int. Conf. on Innovative Techniques and Applications of Artificial Intel. (pp. 255-268). doi:10.1007/978-1-4471-2318-7_20
2010
Multi-Party Argument from Experience
Wardeh, M., Bench-Capon, T., & Coenen, F. (2010). Multi-Party Argument from Experience. In ARGUMENTATION IN MULTI-AGENT SYSTEMS Vol. 6057 (pp. 216-235). Retrieved from https://www.webofscience.com/
Best Clustering Configuration Metrics: Towards Multiagent Based Clustering
Chaimontree, S., Atkinson, K., & Coenen, F. (2010). Best Clustering Configuration Metrics: Towards Multiagent Based Clustering. In Unknown Conference (pp. 48-59). Springer Berlin Heidelberg. doi:10.1007/978-3-642-17316-5_5
Classification Inductive Rule Learning with Negated Features
Chua, S., Coenen, F., & Malcolm, G. (2010). Classification Inductive Rule Learning with Negated Features. In Unknown Conference (pp. 125-136). Springer Berlin Heidelberg. doi:10.1007/978-3-642-17316-5_12
Finding Frequent Subgraphs in Longitudinal Social Network Data Using a Weighted Graph Mining Approach
Jiang, C., Coenen, F., & Zito, M. (2010). Finding Frequent Subgraphs in Longitudinal Social Network Data Using a Weighted Graph Mining Approach. In ADVANCED DATA MINING AND APPLICATIONS, ADMA 2010, PT I Vol. 6440 (pp. 405-416). Retrieved from https://www.webofscience.com/
Frequent Pattern Trend Analysis in Social Networks
Nohuddin, P. N. E., Christley, R., Coenen, F., Patel, Y., Setzkorn, C., & Williams, S. (2010). Frequent Pattern Trend Analysis in Social Networks. In ADVANCED DATA MINING AND APPLICATIONS, ADMA 2010, PT I Vol. 6440 (pp. 358-369). Retrieved from https://www.webofscience.com/
An association rule-based CLIPS program for interactive prediction of MSC differentiation in vitro
Wang, W., Banares-Alcantara, R., Cui, Z., Wang, Y. J., & Coenen, F. (2010). An association rule-based CLIPS program for interactive prediction of MSC differentiation in vitro. In 2010 International Conference on Computer Application and System Modeling (ICCASM 2010). IEEE. doi:10.1109/iccasm.2010.5620726
Frequent Sub-graph Mining on Edge Weighted Graphs
Jiang, C., Coenen, F., & Zito, M. (2010). Frequent Sub-graph Mining on Edge Weighted Graphs. In DATA WAREHOUSING AND KNOWLEDGE DISCOVERY Vol. 6263 (pp. 77-88). Retrieved from https://www.webofscience.com/
Region of Interest Based Image Categorization
Elsayed, A., Coenen, F., García-Fiñana, M., & Sluming, V. (2010). Region of Interest Based Image Categorization. In Lecture Notes in Computer Science (pp. 239-250). Springer Berlin Heidelberg. doi:10.1007/978-3-642-15105-7_19
Clustering in a Multi-Agent Data Mining Environment
Chaimontree, S., Atkinson, K., & Coenen, F. (2010). Clustering in a Multi-Agent Data Mining Environment. In Unknown Conference (pp. 103-114). Springer Berlin Heidelberg. doi:10.1007/978-3-642-15420-1_9
Finding Temporal Patterns in Noisy Longitudinal Data: A Study in Diabetic Retinopathy
Somaraki, V., Broadbent, D., Coenen, F., & Harding, S. (2010). Finding Temporal Patterns in Noisy Longitudinal Data: A Study in Diabetic Retinopathy. In ADVANCES IN DATA MINING: APPLICATIONS AND THEORETICAL ASPECTS Vol. 6171 (pp. 418-+). Retrieved from https://www.webofscience.com/
Hybrid DIAAF/RS: Statistical Textual Feature Selection for Language-Independent Text Classification
Wang, Y. J., Li, F., Coenen, F., Sanderson, R., & Xin, Q. (2010). Hybrid DIAAF/RS: Statistical Textual Feature Selection for Language-Independent Text Classification. In Unknown Conference (pp. 222-236). Springer Berlin Heidelberg. doi:10.1007/978-3-642-14400-4_18
Image Classification Using Histograms and Time Series Analysis: A Study of Age-Related Macular Degeneration Screening in Retinal Image Data
Hijazi, M. H. A., Coenen, F., & Zheng, Y. (2010). Image Classification Using Histograms and Time Series Analysis: A Study of Age-Related Macular Degeneration Screening in Retinal Image Data. In ADVANCES IN DATA MINING: APPLICATIONS AND THEORETICAL ASPECTS Vol. 6171 (pp. 197-+). Retrieved from https://www.webofscience.com/
Multi-Agent Based Clustering: Towards Generic Multi-Agent Data Mining
Chaimontree, S., Atkinson, K., & Coenen, F. (2010). Multi-Agent Based Clustering: Towards Generic Multi-Agent Data Mining. In Unknown Conference (pp. 115-127). Springer Berlin Heidelberg. doi:10.1007/978-3-642-14400-4_9
Trend Mining in Social Networks: A Study Using a Large Cattle Movement Database
Nohuddin, P. N. E., Christley, R., Coenen, F., & Setzkorn, C. (2010). Trend Mining in Social Networks: A Study Using a Large Cattle Movement Database. In ADVANCES IN DATA MINING: APPLICATIONS AND THEORETICAL ASPECTS Vol. 6171 (pp. 464-+). Retrieved from https://www.webofscience.com/
Web-Site Boundary Detection
Alshukri, A., Coenen, F., & Zito, M. (2010). Web-Site Boundary Detection. In ADVANCES IN DATA MINING: APPLICATIONS AND THEORETICAL ASPECTS Vol. 6171 (pp. 529-543). Retrieved from https://www.webofscience.com/
A sliding windows based dual support framework for discovering emerging trends from temporal data
Khan, M. S., Coenen, F., Reid, D., Patel, R., & Archer, L. (2010). A sliding windows based dual support framework for discovering emerging trends from temporal data. Knowledge-Based Systems, 23(4), 316-322. doi:10.1016/j.knosys.2009.11.005
Corpus callosum MR image classification
Elsayed, A., Coenen, F., Jiang, C., García-Fiñana, M., & Sluming, V. (2010). Corpus callosum MR image classification. Knowledge-Based Systems, 23(4), 330-336. doi:10.1016/j.knosys.2009.11.008
Text classification using graph mining-based feature extraction
Jiang, C., Coenen, F., Sanderson, R., & Zito, M. (2010). Text classification using graph mining-based feature extraction. KNOWLEDGE-BASED SYSTEMS, 23(4), 302-308. doi:10.1016/j.knosys.2009.11.010
A Sliding Windows based Dual Support Framework for Discovering Emerging Trends from Temporal Data
Khan, M. S., Coenen, F., Reid, D., Patel, R., & Archer, L. (2010). A Sliding Windows based Dual Support Framework for Discovering Emerging Trends from Temporal Data. In Unknown Conference (pp. 35-48). Springer London. doi:10.1007/978-1-84882-983-1_3
Arguing in Groups
Wardeh, M., Coenen, F., & Bench-Capon, T. (2010). Arguing in Groups. In COMPUTATIONAL MODELS OF ARGUMENT: PROCEEDINGS OF COMMA 2010 Vol. 216 (pp. 475-486). doi:10.3233/978-1-60750-619-5-475
Corpus Callosum MR Image Classification
Elsayed, A., Coenen, F., Jiang, C., García-Fiñana, M., & Sluming, V. (2010). Corpus Callosum MR Image Classification. In Unknown Conference (pp. 333-346). Springer London. doi:10.1007/978-1-84882-983-1_27
Detecting Temporal Pattern and Cluster Changes in Social Networks: A Study Focusing UK Cattle Movement Database
Nohuddin, P. N. E., Coenen, F., Christley, R., & Setzkorn, C. (2010). Detecting Temporal Pattern and Cluster Changes in Social Networks: A Study Focusing UK Cattle Movement Database. In INTELLIGENT INFORMATION PROCESSING V Vol. 340 (pp. 163-+). doi:10.1007/978-3-642-16327-2_22
Detecting temporal pattern and cluster changes in social networks: A study focusing UK cattle movement database
Nohuddin, P. N. E., Coenen, F., Christley, R., & Setzkorn, C. (2010). Detecting temporal pattern and cluster changes in social networks: A study focusing UK cattle movement database. In IFIP Advances in Information and Communication Technology Vol. 340 AICT (pp. 163-172). doi:10.1007/978-3-642-16327-2_22
Image categorisation using time series case based reasoning
Elsayed, A., Hijazi, M. H. A., Coenen, F., Garcia-Finana, M., Sluming, V., & Zheng, Y. (2010). Image categorisation using time series case based reasoning. In UKCBR10 (pp. 2-11). Cambridge: BCS-SGAI.
Region of Interest Based Image Classification using time series analysis
Elsayed, A., Coenen, F., Garcia-Finana, M., & Sluming, V. (2010). Region of Interest Based Image Classification using time series analysis. In The 2010 International Joint Conference on Neural Networks (IJCNN) (pp. 1-6). IEEE. doi:10.1109/ijcnn.2010.5596324
Retinal Image Classification using a Histogram Based Approach
Hijazi, M. H. A., Coenen, F., & Zheng, Y. (2010). Retinal Image Classification using a Histogram Based Approach. In 2010 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS IJCNN 2010. Retrieved from https://www.webofscience.com/
Rule Learning with Negation: Issues Regarding Effectiveness
Chua, S., Coenen, F., & Malcolm, G. (2010). Rule Learning with Negation: Issues Regarding Effectiveness. In Unknown Conference (pp. 193-202). Springer Berlin Heidelberg. doi:10.1007/978-3-642-16327-2_25
Text Classification using Graph Mining-based Feature Extraction
Jiang, C., Coenen, F., Sanderson, R., & Zito, M. (2010). Text Classification using Graph Mining-based Feature Extraction. In RESEARCH AND DEVELOPMENT IN INTELLIGENT SYSTEMS XXVI (pp. 21-34). doi:10.1007/978-1-84882-983-1_2
Text classification using graph mining-based feature extraction
Jiang, C., Coenen, F., Sanderson, R., & Zito, M. (2010). Text classification using graph mining-based feature extraction. In Research and Development in Intelligent Systems XXVI: Incorporating Applications and Innovations in Intelligent Systems XVII (pp. 21-34). doi:10.1007/978-1-84882-983-1_2
Trend Mining in Logitudinal Diabetic Retinopathy Data
Somaraki, V., Broadbent, D., Coenen, F. P., & Harding, S. (2010). Trend Mining in Logitudinal Diabetic Retinopathy Data. In BCS SGAI conference on AI (pp. 285-290). UK: Springer.
2009
Analysis of mesenchymal stem cell differentiation in vitro using classification association rule mining.
Wang, W., Wang, Y. J., Bañares-Alcántara, R., Coenen, F., & Cui, Z. (2009). Analysis of mesenchymal stem cell differentiation in vitro using classification association rule mining.. Journal of bioinformatics and computational biology, 7(6), 905-930. doi:10.1142/s0219720009004424
Application of Classification Association Rule Mining for Mammalian Mesenchymal Stem Cell Differentiation
Wang, W., Wang, Y. J., Bañares-Alcántara, R., Cui, Z., & Coenen, F. (2009). Application of Classification Association Rule Mining for Mammalian Mesenchymal Stem Cell Differentiation. In Unknown Conference (pp. 51-61). Springer Berlin Heidelberg. doi:10.1007/978-3-642-03067-3_6
Effective Mining of Weighted Fuzzy Association Rules
Muyeba, M., Khan, M. S., & Coenen, F. (2010). Effective Mining of Weighted Fuzzy Association Rules. In Rare Association Rule Mining and Knowledge Discovery (pp. 47-64). IGI Global. doi:10.4018/978-1-60566-754-6.ch004
Integrating Data Mining and Agent Based Modeling and Simulation
Baqueiro, O., Wang, Y. J., McBurney, P., & Coenen, F. (2009). Integrating Data Mining and Agent Based Modeling and Simulation. In Unknown Conference (pp. 220-231). Springer Berlin Heidelberg. doi:10.1007/978-3-642-03067-3_18
The EMADS Extendible Multi-Agent Data Mining Framework
Albashiri, K. A., & Coenen, F. (2009). The EMADS Extendible Multi-Agent Data Mining Framework. In Data Mining and Multi-agent Integration (pp. 189-200). Springer US. doi:10.1007/978-1-4419-0522-2_13
A Generic and Extendible Multi-Agent Data Mining Framework
Albashiri, K. A., & Coenen, F. (2009). A Generic and Extendible Multi-Agent Data Mining Framework. In Unknown Conference (pp. 203-210). Springer Berlin Heidelberg. doi:10.1007/978-3-642-02319-4_24
A Hybrid Statistical Data Pre-processing Approach for Language-Independent Text Classification
Wang, Y. J., Coenen, F., & Sanderson, R. (2009). A Hybrid Statistical Data Pre-processing Approach for Language-Independent Text Classification. In Unknown Conference (pp. 338-349). Springer Berlin Heidelberg. doi:10.1007/978-3-642-03348-3_33
EMADS: An extendible multi-agent data miner
Albashiri, K. A., Coenen, F., & Leng, P. (2009). EMADS: An extendible multi-agent data miner. Knowledge-Based Systems, 22(7), 523-528. doi:10.1016/j.knosys.2008.10.009
Arguing from Experience to Classifying Noisy Data
Wardeh, M., Coenen, F., & Bench-Capon, T. (2009). Arguing from Experience to Classifying Noisy Data. In DATA WAREHOUSING AND KNOWLEDGE DISCOVERY, PROCEEDINGS Vol. 5691 (pp. 354-365). Retrieved from https://www.webofscience.com/
Agent-Enriched Data Mining Using an Extendable Framework
Albashiri, K. A., & Coenen, F. (2009). Agent-Enriched Data Mining Using an Extendable Framework. In Unknown Conference (pp. 53-68). Springer Berlin Heidelberg. doi:10.1007/978-3-642-03603-3_5
PADUA: a protocol for argumentation dialogue using association rules
Wardeh, M., Bench-Capon, T., & Coenen, F. (2009). PADUA: a protocol for argumentation dialogue using association rules. Artificial Intelligence and Law, 17(3), 183-215. doi:10.1007/s10506-009-9078-8
Improved methods for extracting frequent itemsets from interim‐support trees
Coenen, F., Leng, P., Pagourtzis, A., Rytter, W., & Souliou, D. (2009). Improved methods for extracting frequent itemsets from interim‐support trees. Software: Practice and Experience, 39(6), 551-571. doi:10.1002/spe.902
A Framework for Mining Fuzzy Association Rules from Composite Items
Muyeba, M., Khan, M. S., & Coenen, F. (2009). A Framework for Mining Fuzzy Association Rules from Composite Items. In Unknown Conference (pp. 62-74). Springer Berlin Heidelberg. doi:10.1007/978-3-642-00399-8_6
A Histogram Based Approach to Screening of Age-related Macular Degeneration
Hijazi, M. H. A., Coenen, F. P., & Zheng, Y. (2009). A Histogram Based Approach to Screening of Age-related Macular Degeneration. In MIUA'09 (pp. 54-158). Warwick: MIUA.
Agent-Enriched Data Mining Using an Extendable Framework
Albashiri, K. A., & Coenen, F. P. (2009). Agent-Enriched Data Mining Using an Extendable Framework. In ADMI (pp. 89-106). Budapest: AAMAS.
An investigation into the issues of Multi-Agent Data Mining
Albashiri, K. A., & Coenen, F. P. (2009). An investigation into the issues of Multi-Agent Data Mining. In D. Bouça, & A. Gafagnão (Eds.), Agent Based Comnputing (pp. 1-85). Hauppauge, NY, USA: Nova Science Publishers.
Construction and Application of a Public-Domain Mesenchymal Stem Cell Database
Wang, W., Bañares-Alcántara, R., Cui, Z., Wang, Y., & Coenen, F. P. (2009). Construction and Application of a Public-Domain Mesenchymal Stem Cell Database. In ISBME'09 (pp. 78). Bangkok: IEEE.
EMADS: An Extendible Multi-Agent Data Miner
Albashiri, K. A., Coenen, F., & Leng, P. (2009). EMADS: An Extendible Multi-Agent Data Miner. In Unknown Conference (pp. 263-275). Springer London. doi:10.1007/978-1-84882-171-2_19
Fuzzy Weighted Association Rule Mining with Weighted Support and Confidence Framework
Muyeba, M., Khan, M. S., & Coenen, F. (2009). Fuzzy Weighted Association Rule Mining with Weighted Support and Confidence Framework. In Unknown Conference (pp. 49-61). Springer Berlin Heidelberg. doi:10.1007/978-3-642-00399-8_5
Graph-based Image Classification by Weighting Scheme
Jiang, C., & Coenen, F. (2009). Graph-based Image Classification by Weighting Scheme. In Unknown Conference (pp. 63-76). Springer London. doi:10.1007/978-1-84882-215-3_5
Mining Allocating Patterns in Investment Portfolios
Wang, Y. J., Zheng, X., & Coenen, F. (2009). Mining Allocating Patterns in Investment Portfolios. In Database Technologies (pp. 2657-2684). IGI Global. doi:10.4018/978-1-60566-058-5.ch159
Mining Allocating Patterns in Investment Portfolios
Wang, Y. J., Zheng, X., & Coenen, F. (2009). Mining Allocating Patterns in Investment Portfolios. In Data Mining Applications for Empowering Knowledge Societies (pp. 110-135). IGI Global. doi:10.4018/978-1-59904-657-0.ch007
Multi-Party Argument from Experience
Wardeh, M., Bench-Capon, T., & Coenen, F. P. (2009). Multi-Party Argument from Experience. In ARGMAS'09 (pp. 207-224). Budapest: AAMAS.
PISA — Pooling Information from Several Agents: Multiplayer Argumentation from Experience
Wardeh, M., Bench-Capon, T., & Coenen, F. (2009). PISA — Pooling Information from Several Agents: Multiplayer Argumentation from Experience. In Unknown Conference (pp. 133-146). Springer London. doi:10.1007/978-1-84882-171-2_10
The EMADS Extendible Multi-Agent Data Mining Framework
Albashiri, K. A., & Coenen, F. P. (2009). The EMADS Extendible Multi-Agent Data Mining Framework. In L. Cao (Ed.), Data Mining and Multiagent Integration (pp. 89-200). Berlin: Springer.
2008
On extraction of Nutritional Patterns (NPS) using fuzzy association rule mining
Khan, M. S., Muyeba, M., & Coenen, F. (2008). On extraction of Nutritional Patterns (NPS) using fuzzy association rule mining. In HEALTHINF 2008 - 1st International Conference on Health Informatics, Proceedings Vol. 1 (pp. 34-42).
Measuring and Explaining the Quality of Web Sites in the (Virtual) House of Representatives
Esterling, K. M., Lazer, D. M. J., & Neblo, M. A. (2007). Measuring and Explaining the Quality of Web Sites in the (Virtual) House of Representatives. In Current Issues and Trends in E-Government Research (pp. 146-162). IGI Global. doi:10.4018/978-1-59904-283-1.ch007
Mining Allocating Patterns in One-Sum Weighted Items
Wang, Y. J., Zheng, X., Coenen, F., & Li, C. Y. (2008). Mining Allocating Patterns in One-Sum Weighted Items. In 2008 IEEE International Conference on Data Mining Workshops (pp. 592-598). IEEE. doi:10.1109/icdmw.2008.112
A Weighted Utility Framework for Mining Association Rules
Khan, M. S., Muyeba, M., & Coenen, F. (2008). A Weighted Utility Framework for Mining Association Rules. In 2008 Second UKSIM European Symposium on Computer Modeling and Simulation (pp. 87-92). IEEE. doi:10.1109/ems.2008.73
Document-Base Extraction for Single-Label Text Classification
Wang, Y. J., Sanderson, R., Coenen, F., & Leng, P. (n.d.). Document-Base Extraction for Single-Label Text Classification. In Unknown Conference (pp. 357-367). Springer Berlin Heidelberg. doi:10.1007/978-3-540-85836-2_34
Mining Efficiently Significant Classification Association Rules
Wang, Y. J., Xin, Q., & Coenen, F. (2008). Mining Efficiently Significant Classification Association Rules. Unknown Journal, 443-467. doi:10.1007/978-3-540-78488-3_26
Weighted Association Rule Mining from Binary and Fuzzy Data
Khan, M. S., Muyeba, M., & Coenen, F. (n.d.). Weighted Association Rule Mining from Binary and Fuzzy Data. In Unknown Conference (pp. 200-212). Springer Berlin Heidelberg. doi:10.1007/978-3-540-70720-2_16
Agent Based Frequent Set Meta Mining: Introducing EMADS
Albashiri, K. A., Coenen, F., & Leng, P. (n.d.). Agent Based Frequent Set Meta Mining: Introducing EMADS. In Unknown Conference (pp. 23-32). Springer US. doi:10.1007/978-0-387-09695-7_3
Mining Fuzzy Association Rules from Composite Items
Khan, M. S., Muyeba, M., & Coenen, F. (n.d.). Mining Fuzzy Association Rules from Composite Items. In Unknown Conference (pp. 67-76). Springer US. doi:10.1007/978-0-387-09695-7_7
A Framework for Mining Fuzzy Association Rules from Composite Items", Algorithms for
Khan, M. S., Muyeba, M., & Coenen, F. P. (2008). A Framework for Mining Fuzzy Association Rules from Composite Items", Algorithms for. In ASLIP'08 (pp. 65-77). Osaka: PAKDD.
Argument Based Moderation of Benefit Assessment
Wardeh, M., Bench-Capon, T. J. M., & Coenen, F. (2008). Argument Based Moderation of Benefit Assessment. In LEGAL KNOWLEDGE AND INFORMATION SYSTEMS Vol. 189 (pp. 128-137). doi:10.3233/978-1-58603-952-3-128
Arguments from Experience: The PADUA Protocol
Wardeh, M., Bench-Capon, T., & Coenen, F. (2008). Arguments from Experience: The PADUA Protocol. In COMPUTATIONAL MODELS OF ARGUMENT, PROCEEDINGS OF COMMA 2008 Vol. 172 (pp. 405-416). Retrieved from https://www.webofscience.com/
Efficiently Mining Significant Classification Association Rules
Wang, Y. J., Xin, Q., & Coenen, F. P. (2008). Efficiently Mining Significant Classification Association Rules. In T. Y. Lin, A. Wasilewska, F. Petry, & Y. Xie (Eds.), Data Mining: Foundations and Practice (pp. 443-468). Heidelberg: Springer.
Fuzzy Weighted Association Rule Mining with Weighted Support and Confidence Framework
Khan, M. S., Muyeba, M., & Coenen, F. P. (2008). Fuzzy Weighted Association Rule Mining with Weighted Support and Confidence Framework. In ASLIP'08 (pp. 53-64). Osaka: PAKDD.
Hybrid Rule Ordering in Classification Association Rule Mining
Wang, Y. J., Xin, Q., & Coenen, F. P. (2008). Hybrid Rule Ordering in Classification Association Rule Mining. Transactions on Machine Learning and Data Mining in Pattern Recognition, 1-16.
Mining fuzzy association rules from composite items
Sulaiman Khan, M., Muyeba, M., & Coenen, F. (2008). Mining fuzzy association rules from composite items. In IFIP Advances in Information and Communication Technology Vol. 276 (pp. 67-76).
Research and Development in Intelligent Systems XXV
Bramer, M., Coenen, F. P., & Petridis, M. (Eds.) (2008). Research and Development in Intelligent Systems XXV. In AI'2008 (pp. 300). Cambridge: Springer.
The PADUA Protocol
Wardeh, M., Bench-Capon, T., & Coenen, F. (2008). The PADUA Protocol. In COMMA 2008 (pp. 405-416). Toulouse: IOS Press.
2007
A Novel Rule Weighting Approach in Classification Association Rule Mining
Wang, Y. J., Xin, Q., & Coenen, F. (2007). A Novel Rule Weighting Approach in Classification Association Rule Mining. In Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007) (pp. 271-276). IEEE. doi:10.1109/icdmw.2007.126
The effect of threshold values on association rule based classification accuracy
Coenen, F., & Leng, P. (2007). The effect of threshold values on association rule based classification accuracy. Data & Knowledge Engineering, 60(2), 345-360. doi:10.1016/j.datak.2006.02.005
'A Novel Rule Weighting Approach in Classification Association Rule Mining'
Wang, J., Xin, Q., & Coenen, F. P. (2007). 'A Novel Rule Weighting Approach in Classification Association Rule Mining'. In ICSM'07 Workshop (pp. x). Nebraska, USA: IEEE.
'Association Rule Mining in The Wider Context of Text, Images and Graphs.'
Coenen, F. (2007). 'Association Rule Mining in The Wider Context of Text, Images and Graphs.'. Expert Upda, 9(3), 5-9.
A Novel Rule Ordering Approach in Classification Association Rule Mining
Wang, Y. J., Xin, Q., & Coenen, F. (n.d.). A Novel Rule Ordering Approach in Classification Association Rule Mining. In Unknown Conference (pp. 339-348). Springer Berlin Heidelberg. doi:10.1007/978-3-540-73499-4_26
An effective fuzzy health rule mining algorithm.
Khan, M. S., Muyeba, M., Tjortjis, C., & Coenen, F. P. (2007). An effective fuzzy health rule mining algorithm.. In Proc. 7th Annual Workshop on Computational Intelligence (pp. xx). Aberdeen: University of Aberdeen.
Association Rule Mining in The Wider Context of Text, Images and Graphs.
Coenen, F. P. (2007). Association Rule Mining in The Wider Context of Text, Images and Graphs.. In UKKDD'7 (pp. 1-6). Canterbury: University of Kent.
Dynamic Rule Mining for Argumentation Based Systems
Wardeh, M., Bench-Capon, T., & Coenen, F. (n.d.). Dynamic Rule Mining for Argumentation Based Systems. In Unknown Conference (pp. 65-78). Springer London. doi:10.1007/978-1-84800-094-0_6
Frequent Set Meta Mining: Towards Multi-Agent Data Mining
Albashiri, K. A., Coenen, F., Sanderson, R., & Leng, P. (n.d.). Frequent Set Meta Mining: Towards Multi-Agent Data Mining. In Unknown Conference (pp. 139-151). Springer London. doi:10.1007/978-1-84800-094-0_11
PADUA protocol:TB Strategies and tactics
Wardeh, M., Bench-Capon, T., & Coenen, F. (2007). PADUA protocol:TB Strategies and tactics. In SYMBOLIC AND QUANTITATIVE APPROACHES TO REASONING WITH UNCERTAINTY, PROCEEDINGS Vol. 4724 (pp. 465-+). Retrieved from https://www.webofscience.com/
Research and Development in Intelligent Systems XXIV
Bramer, M., Coenen, F. P., & Petridis, M. (Eds.) (2007). Research and Development in Intelligent Systems XXIV. In AI'2007 (pp. 200). London: Springer.
Statistical Identification of Key Phrases for Text Classification
Coenen, F., Leng, P., Sanderson, R., & Wang, Y. J. (n.d.). Statistical Identification of Key Phrases for Text Classification. In Unknown Conference (pp. 838-853). Springer Berlin Heidelberg. doi:10.1007/978-3-540-73499-4_63
Text Classification using Language-independent Pre-processing
Wang, Y. J., Coenen, F., Leng, P., & Sanderson, R. (2007). Text Classification using Language-independent Pre-processing. In Unknown Conference (pp. 413-417). Springer London. doi:10.1007/978-1-84628-663-6_34
2006
Towards an Agent-Based Framework for Online After-Sale Services
Lu Zhang., Coenen, F., Huang, W., & Leng, P. (2006). Towards an Agent-Based Framework for Online After-Sale Services. In 2006 3rd International IEEE Conference Intelligent Systems (pp. 420-425). IEEE. doi:10.1109/is.2006.348456
Tree-based partitioning of date for association rule mining
Ahmed, S., Coenen, F., & Leng, P. (2006). Tree-based partitioning of date for association rule mining. Knowledge and Information Systems, 10(3), 315-331. doi:10.1007/s10115-006-0010-1
The Knowledge Bazaar
Craker, B., & Coenen, F. (2006). The Knowledge Bazaar. Knowledge-Based Systems, 19(5), 341-347. doi:10.1016/j.knosys.2005.11.019
Partitioning strategies for distributed association rule mining
COENEN, F., & LENG, P. (2006). Partitioning strategies for distributed association rule mining. The Knowledge Engineering Review, 21(1), 25-47. doi:10.1017/s0269888906000786
Improved Methods for Extracting Frequent Itemsets from Interim-Support Trees
Coenen, F., Leng, P., Pagourtzis, A., Rytter, W., & Souliou, D. (2006). Improved Methods for Extracting Frequent Itemsets from Interim-Support Trees. In Unknown Conference (pp. 263-276). Springer London. doi:10.1007/978-1-84628-226-3_20
Research and Development in Intelligent Systems XXIII
Bramer, M., Coenen, F., & Tueson, A. (Eds.) (2006). Research and Development in Intelligent Systems XXIII. In AI'2006 (pp. 419). London: Springer..
Towards an Agent-Based Framework for Online After-Sale Services.
Zhang, L., Coenen, F. P., Huang, W., & Leng, P. H. (2006). Towards an Agent-Based Framework for Online After-Sale Services.. In IEEE Conference On Intelligent Systems (pp. 06EX1304C). London: IEEE.
2005
Obtaining Best Parameter Values for Accurate Classification
Coenen, F., & Leng, P. (n.d.). Obtaining Best Parameter Values for Accurate Classification. In Fifth IEEE International Conference on Data Mining (ICDM'05) (pp. 597-600). IEEE. doi:10.1109/icdm.2005.105
'Selection of Significant Rules in Classification Association Rule Mining'
Wang, Y. J., Qin, X., & Coenen, F. (2005). 'Selection of Significant Rules in Classification Association Rule Mining'. In ICDM 2005 (pp. 106-108). Houston: Saint Mary's University, Halifax, Canada.
Proceedings 25th BCS-SGAI AI Conference: Research and Development in Intelligent Systems XXII
Bramer, M., Coenen, F., & Allen, T. (Eds.) (2005). Proceedings 25th BCS-SGAI AI Conference: Research and Development in Intelligent Systems XXII. In AI'2005 (pp. 9999). London: Springer.
Proceedings of the first UK Knowledge Discovery in Data Symposium
Coenen, F. (Ed.) (2005). Proceedings of the first UK Knowledge Discovery in Data Symposium. In UKKDD'05 (pp. 9999). Liverpool: Dept of Computer Science, University of Liverpool.
The Knowledge Bazaar
Craker, B., & Coenen, F. (n.d.). The Knowledge Bazaar. In Unknown Conference (pp. 37-49). Springer London. doi:10.1007/1-84628-224-1_4
Threshold Tuning for Improved Classification Association Rule Mining
Coenen, F., Leng, P., & Zhang, L. (2005). Threshold Tuning for Improved Classification Association Rule Mining. In Unknown Conference (pp. 216-225). Springer Berlin Heidelberg. doi:10.1007/11430919_27
2004
An Evaluation of Approaches to Classification Rule Selection
Coenen, F., & Leng, P. (n.d.). An Evaluation of Approaches to Classification Rule Selection. In Fourth IEEE International Conference on Data Mining (ICDM'04) (pp. 359-362). IEEE. doi:10.1109/icdm.2004.10012
Data structure for association rule mining: T-trees and P-trees
Coenen, F., Leng, P., & Ahmed, S. (2004). Data structure for association rule mining: T-trees and P-trees. IEEE Transactions on Knowledge and Data Engineering, 16(6), 774-778. doi:10.1109/tkde.2004.8
A Tree Partitioning Method for Memory Management in Association Rule Mining
Ahmed, S., Coenen, F., & Leng, P. (2004). A Tree Partitioning Method for Memory Management in Association Rule Mining. Unknown Journal, 331-340. doi:10.1007/978-3-540-30076-2_33
Strategies for Partitioning Data in Association Rule Mining
Ahmed, S., Coenen, F., & Leng, P. (2004). Strategies for Partitioning Data in Association Rule Mining. In Research and Development in Intelligent Systems XX (pp. 127-139). Springer London. doi:10.1007/978-0-85729-412-8_10
Tree Structures for Mining Association Rules
Coenen, F., Goulbourne, G., & Leng, P. (2004). Tree Structures for Mining Association Rules. Data Mining and Knowledge Discovery, 8(1), 25-51. doi:10.1023/b:dami.0000005257.93780.3b
Using Domain Knowledge to Boost Case-Based Diagnosis: An Experimental Study in a Domain with Very Poor Data Quality
Zhang, L., Coenen, F., & Leng, P. (2004). Using Domain Knowledge to Boost Case-Based Diagnosis: An Experimental Study in a Domain with Very Poor Data Quality. In Applications and Innovations in Intelligent Systems XI (pp. 137-151). Springer London. doi:10.1007/978-1-4471-0643-2_10
2003
T-trees, vertical partitioning and distributed association rule mining
Coenen, F., Leng, P., & Ahmed, S. (n.d.). T-trees, vertical partitioning and distributed association rule mining. In Third IEEE International Conference on Data Mining (pp. 513-516). IEEE Comput. Soc. doi:10.1109/icdm.2003.1250965
Setting attribute weights for k-NN based binary classification via quadratic programming
Zhang, L., Coenen, F., & Leng, P. (2003). Setting attribute weights for k-NN based binary classification via quadratic programming. Intelligent Data Analysis, 7(5), 427-441. doi:10.3233/ida-2003-7504
2002
Formalising optimal feature weight setting in case based diagnosis as linear programming problems
Zhang, L., Coenen, F., & Leng, P. (2002). Formalising optimal feature weight setting in case based diagnosis as linear programming problems. Knowledge-Based Systems, 15(7), 391-398. doi:10.1016/s0950-7051(02)00023-0
5th European conference on principles of knowledge discovery in databases
COENEN, F. (2002). 5th European conference on principles of knowledge discovery in databases. In The Knowledge Engineering Review Vol. 17 (pp. 197-203). Cambridge University Press (CUP). doi:10.1017/s026988890200022x
An Experimental Study of Increasing Diversity for Case-Based Diagnosis
Zhang, L., Coenen, F., & Leng, P. (2002). An Experimental Study of Increasing Diversity for Case-Based Diagnosis. In Unknown Conference (pp. 448-459). Springer Berlin Heidelberg. doi:10.1007/3-540-46119-1_33
Finding Association Rules with Some Very Frequent Attributes
Coenen, F., & Leng, P. (2002). Finding Association Rules with Some Very Frequent Attributes. In Unknown Conference (pp. 99-111). Springer Berlin Heidelberg. doi:10.1007/3-540-45681-3_9
Optimising Association Rule Algorithms Using Itemset Ordering
Coenen, F., & Leng, P. (2002). Optimising Association Rule Algorithms Using Itemset Ordering. In Research and Development in Intelligent Systems XVIII (pp. 53-66). Springer London. doi:10.1007/978-1-4471-0119-2_5
2001
Toward logical analysis of tabular rule-based systems
Lig?za, A. (2001). Toward logical analysis of tabular rule-based systems. International Journal of Intelligent Systems, 16(3), 333-360. doi:3.0.co;2-r">10.1002/1098-111x(200103)16:3<333::aid-int1011>3.0.co;2-r
An Architecture For Web-based Post-sales Service In A Flexible Manufacturing Environment
Zhang, W., Coenen, F., & Leng, P. (n.d.). An Architecture For Web-based Post-sales Service In A Flexible Manufacturing Environment. In Unknown Conference (pp. 407-416). Kluwer Academic Publishers. doi:10.1007/0-306-47009-8_29
Computing Association Rules Using Partial Totals
Coenen, F., Goulbourne, G., & Leng, P. (2001). Computing Association Rules Using Partial Totals. In Unknown Conference (pp. 54-66). Springer Berlin Heidelberg. doi:10.1007/3-540-44794-6_5
Towards Integrated Online Support for Field Service Engineers in a Flexible Manufacturing Context
Coenen, F., Leng, P., Weaver, R., & Zhang, W. (2001). Towards Integrated Online Support for Field Service Engineers in a Flexible Manufacturing Context. In Applications and Innovations in Intelligent Systems VIII (pp. 141-152). Springer London. doi:10.1007/978-1-4471-0275-5_11
Verification, validation, and integrity issues in expert and database systems: Two perspectives
Coenen, F., Eaglestone, B., & Ridley, M. (2001). Verification, validation, and integrity issues in expert and database systems: Two perspectives. International Journal of Intelligent Systems, 16(3), 425-447. doi:3.0.co;2-c">10.1002/1098-111x(200103)16:3<425::aid-int1016>3.0.co;2-c
2000
Spatial reasoning: improving computational efficiency
Brown, A. G. P., & Coenen, F. P. (2000). Spatial reasoning: improving computational efficiency. AUTOMATION IN CONSTRUCTION, 9(4), 361-367. doi:10.1016/S0926-5805(99)00019-9
Validation and verification of knowledge-based systems:: report on EUROVAV99
Coenen, F., Bench-Capon, T., Boswell, R., Dibie-Barthélemy, J., Eaglestone, B., Gerrits, R., . . . Wiratunga, N. (2000). Validation and verification of knowledge-based systems:: report on EUROVAV99. KNOWLEDGE ENGINEERING REVIEW, 15(2), 187-196. doi:10.1017/S0269888900002010
Algorithms for Computing Association Rules Using a Partial-Support Tree
Goulbourne, G., Coenen, F., & Leng, P. (2000). Algorithms for Computing Association Rules Using a Partial-Support Tree. In Research and Development in Intelligent Systems XVI (pp. 132-147). Springer London. doi:10.1007/978-1-4471-0745-3_9
Algorithms for computing association rules using a partial-support tree
Goulbourne, G., Coenen, F., & Leng, P. (2000). Algorithms for computing association rules using a partial-support tree. Knowledge-Based Systems, 13(2-3), 141-149. doi:10.1016/s0950-7051(00)00055-1
An experiment in discovering association rules in the legal domain
Bench-Capon, T., Coenen, F., & Leng, P. (2000). An experiment in discovering association rules in the legal domain. In 11TH INTERNATIONAL WORKSHOP ON DATABASE AND EXPERT SYSTEMS APPLICATION, PROCEEDINGS (pp. 1056-1060). doi:10.1109/DEXA.2000.875157
Tesseral spatio-temporal reasoning for multi-dimensional data
Coenen, F. (2000). Tesseral spatio-temporal reasoning for multi-dimensional data. Pattern Recognition, 33(1), 9-23. doi:10.1016/s0031-3203(99)00039-4
The improvement of response modeling: combining rule-induction and case-based reasoning
Coenen, F., Swinnen, G., Vanhoof, K., & Wets, G. (2000). The improvement of response modeling: combining rule-induction and case-based reasoning. Expert Systems with Applications, 18(4), 307-313. doi:10.1016/s0957-4174(00)00012-9
1999
Report on the 1st international workshop on validation, verification and integrity issues of expert and database systems
Bench-Capon, T., Castelli, D., Coenen, F., Devendeville-Brisoux, L., Eaglestone, B., Fiddian, N., . . . Vermesan, A. (1999). Report on the 1st international workshop on validation, verification and integrity issues of expert and database systems. Information Research, 4(3), 54-59.
A Generic Ontology for Spatial Reasoning
Coenen, F., & Visser, P. (1999). A Generic Ontology for Spatial Reasoning. In Research and Development in Expert Systems XV (pp. 44-57). Springer London. doi:10.1007/978-1-4471-0835-1_4
Developing Association Rules in Facilities Management Databases
Goulbourne, G., Coenen, F., Leng, P., & Murphy, D. (1999). Developing Association Rules in Facilities Management Databases. In Applications and Innovations in Expert Systems VI (pp. 230-244). Springer London. doi:10.1007/978-1-4471-0575-6_17
Multi-dimensional tesseral spatial reasoning for noise pollution modelling
Coenen, F., Shave, M., Brown, A., & Lewis, J. (1999). Multi-dimensional tesseral spatial reasoning for noise pollution modelling. ADVANCES IN ENGINEERING SOFTWARE, 30(7), 479-488. doi:10.1016/S0965-9978(99)00004-6
Region description and comparative analysis using a tesseral representation
Antonacopoulos, A., & Coenen, F. P. (1999). Region description and comparative analysis using a tesseral representation. In Proceedings of the Fifth International Conference on Document Analysis and Recognition. ICDAR '99 (Cat. No.PR00318) (pp. 193-196). IEEE. doi:10.1109/icdar.1999.791757
The Improvement of Response Modeling: Combining Rule-Induction and Case-Based Reasoning
Coenen, F., Swinnen, G., Vanhoof, K., & Wets, G. (1999). The Improvement of Response Modeling: Combining Rule-Induction and Case-Based Reasoning. In Unknown Conference (pp. 301-308). Springer Berlin Heidelberg. doi:10.1007/978-3-540-48247-5_34
Validation, Verification and Integrity in Knowledge and Data Base Systems: Future Directions
Coenen, F., Eaglestone, B., & Ridley, M. (1999). Validation, Verification and Integrity in Knowledge and Data Base Systems: Future Directions. In Validation and Verification of Knowledge Based Systems (pp. 297-311). Springer US. doi:10.1007/978-1-4757-6916-6_20
Visualisation of an AI Solution
Brown, A. G. P., Coenen, F. P., & Knight, M. W. (1999). Visualisation of an AI Solution. In Visual Representations and Interpretations (pp. 367-374). Springer London. doi:10.1007/978-1-4471-0563-3_41
1998
KD in FM: Knowledge discovery in facilities management databases
Goulbourne, G., Coenen, F., & Leng, P. (1998). KD in FM: Knowledge discovery in facilities management databases. In Unknown Conference (pp. 806-815). Springer Berlin Heidelberg. doi:10.1007/bfb0054536
Rulebase checking using a spatial representation
Coenen, F. (1998). Rulebase checking using a spatial representation. In Unknown Conference (pp. 166-175). Springer Berlin Heidelberg. doi:10.1007/bfb0054478
Spatial reasoning using the quad tesseral representation
Coenen, F. P., Beattie, B., Shave, M. J. R., Bench-Capon, T. J. M., & Diaz, B. M. (1998). Spatial reasoning using the quad tesseral representation. ARTIFICIAL INTELLIGENCE REVIEW, 12(4), 321-343. doi:10.1023/A:1006541105578
1997
An AI Approach to Noise Prediction
Brown, A. G. P., Coenen, F. P., Shave, M. J., & Knight, M. W. (1997). An AI Approach to Noise Prediction. Building Acoustics, 4(2), 137-150. doi:10.1177/1351010x9700400205
A tesseral approach to N-dimensional spatial reasoning
Coenen, F. P., Beattie, B., Bench-Capon, T. J. M., Diaz, B. M., & Shave, M. J. R. (1997). A tesseral approach to N-dimensional spatial reasoning. In Unknown Conference (pp. 633-642). Springer Berlin Heidelberg. doi:10.1007/bfb0022071
Coordinating Human and Software Agents through Electronic Mail
Finch, I., Coenen, F., Bench-Capon, T., & Shave, M. (1997). Coordinating Human and Software Agents through Electronic Mail. In Computer Supported Cooperative Work (pp. 64-78). Springer London. doi:10.1007/978-1-4471-3042-0_4
1996
An ontology for linear spatial reasoning
Coenen, F., Beattie, B., BenchCapon, T. J. M., Shave, M. J. R., & Diaz, B. M. (1996). An ontology for linear spatial reasoning. In DATABASE AND EXPERT SYSTEMS APPLICATIONS Vol. 1134 (pp. 718-727). Retrieved from https://www.webofscience.com/
Temporal reasoning using tesseral addressing: Towards an intelligent environmental impact assessment system
Coenen, F., Beattie, B., Diaz, B., BenchCapon, T. J. M., & Shave, M. J. R. (1996). Temporal reasoning using tesseral addressing: Towards an intelligent environmental impact assessment system. KNOWLEDGE-BASED SYSTEMS, 9(5), 287-300. doi:10.1016/0950-7051(96)01036-2
1995
Using cooperating knowledge-based systems to reduce information overload
Finch, I., Coenen, F., Bench-Capon, T., & Shave, M. (1995). Using cooperating knowledge-based systems to reduce information overload. In IEE Colloquium (Digest).
Advanced binary encoded matrix representation for rule base verification
Coenen, F. (1995). Advanced binary encoded matrix representation for rule base verification. Knowledge-Based Systems, 8(4), 201-210. doi:10.1016/0950-7051(95)96217-f
Developing distributed database applications using TSL
Coenen, F. P., Finch, I., Shave, M. J. R., & Bench-Capon, T. J. M. (1995). Developing distributed database applications using TSL. In Unknown Conference (pp. 58-67). Springer Berlin Heidelberg. doi:10.1007/bfb0049105
Spatial reasoning for GIS using a tesseral data representation
Beattie, B., Coenen, F., Bench-Capon, T. J. M., Diaz, B. M., & Shave, M. J. R. (1995). Spatial reasoning for GIS using a tesseral data representation. In Unknown Conference (pp. 207-216). Springer Berlin Heidelberg. doi:10.1007/bfb0049119
1994
A binary encoded incidence matrix representation for KBS Verification
Coenen, F. (1994). A binary encoded incidence matrix representation for KBS Verification. Robotics and Computer-Integrated Manufacturing, 11(3), 221-232. doi:10.1016/0736-5845(94)90037-x
1993
Representing visual conditions in a legal knowledge based system
Coenen, F., Bench-Capon, T., & Smeaton, P. (1993). Representing visual conditions in a legal knowledge based system. In Proceedings of the fourth international conference on Artificial intelligence and law - ICAIL '93 (pp. 264-271). ACM Press. doi:10.1145/158976.159009
Argument‐based explanation of the British nationality act as a logic program
Bench‐Capon, T., Coenen, F., & Orton, P. (1993). Argument‐based explanation of the British nationality act as a logic program. Information & Communications Technology Law, 2(1), 53-66. doi:10.1080/13600834.1993.9965668
EXPERT-SYSTEM SUPPORT FOR TEAMS OF MOBILE DISTRIBUTED ENGINEERS
COENEN, F., BENCHCAPON, T. J. M., SHAVE, M. J. R., & FINCH, I. (1993). EXPERT-SYSTEM SUPPORT FOR TEAMS OF MOBILE DISTRIBUTED ENGINEERS. In APPLICATIONS OF ARTIFICIAL INTELLIGENCE IN ENGINEERING VIII, VOL 1 (pp. 491-504). Retrieved from https://www.webofscience.com/
Two aspects of the validation and verification of knowledge-based systems
Bench-Capon, T., Coenen, F., Nwana, H. S., Paton, R., & Shave, M. (1993). Two aspects of the validation and verification of knowledge-based systems. IEEE Expert, 8(3), 76-81. doi:10.1109/64.215226
Using allspeak to reverse engineer KBS specifications
Threadgold, R., & Coenen, F. (1993). Using allspeak to reverse engineer KBS specifications. In Applications of Artificial Intelligence in Engineering Vol. 2 (pp. 61-76).
Verification of rule-bases using incidence matrices: The IMVER system
Coenen, F., Taleb-Bendiab, A., & Forster, R. (1993). Verification of rule-bases using incidence matrices: The IMVER system. In Applications of Artificial Intelligence in Engineering Vol. 1 (pp. 247-260).
1992
KBS MAINTENANCE VALIDATION USING SIMULATION
COENEN, F., & BENCHCAPON, T. J. M. (1992). KBS MAINTENANCE VALIDATION USING SIMULATION. In APPLICATIONS OF ARTIFICIAL INTELLIGENCE IN ENGINEERING VII (pp. 215-228). Retrieved from https://www.webofscience.com/
THE MAINTENANCE OF LEGAL KNOWLEDGE BASED SYSTEMS
BENCHCAPON, T., & COENEN, F. (1992). THE MAINTENANCE OF LEGAL KNOWLEDGE BASED SYSTEMS. ARTIFICIAL INTELLIGENCE REVIEW, 6(2), 129-143. doi:10.1007/BF00150230
Isomorphism and legal knowledge based systems
Bench-Capon, T. J. M., & Coenen, F. P. (1992). Isomorphism and legal knowledge based systems. Artificial Intelligence and Law, 1(1), 65-86. doi:10.1007/bf00118479
Building Knowledge Based Systems for Maintainability
Coenen, F., & Bench-Capon, T. (1992). Building Knowledge Based Systems for Maintainability. In Database and Expert Systems Applications (pp. 415-420). Springer Vienna. doi:10.1007/978-3-7091-7557-6_71
Electronic Chart Representation and Interaction
Coenen, F., Fawcett, S., Smeaton, P., & Bench-Capon, T. (1992). Electronic Chart Representation and Interaction. In Database and Expert Systems Applications (pp. 543). Springer Vienna. doi:10.1007/978-3-7091-7557-6_92
INTEGRATING LEGAL SUPPORT SYSTEMS THROUGH DOCUMENT MODELS
BENCHCAPON, T. J. M., COENEN, F., & DUNNE, P. E. S. (1992). INTEGRATING LEGAL SUPPORT SYSTEMS THROUGH DOCUMENT MODELS. EXPERT SYSTEMS WITH APPLICATIONS, 4(4), 355-362. doi:10.1016/0957-4174(92)90128-F
MAINTENANCE TOOLS FOR KNOWLEDGE-BASED SYSTEMS - THE MAKE PROJECT
BENCHCAPON, T., & COENEN, F. (1992). MAINTENANCE TOOLS FOR KNOWLEDGE-BASED SYSTEMS - THE MAKE PROJECT. EXPERT SYSTEMS WITH APPLICATIONS, 5(3-4), 267-273. doi:10.1016/0957-4174(92)90011-G
1991
A Graphical Interactive Tool for KBS Maintenance
Coenen, F., & Bench-Capon, T. (1991). A Graphical Interactive Tool for KBS Maintenance. In Database and Expert Systems Applications (pp. 166-171). Springer Vienna. doi:10.1007/978-3-7091-7555-2_28
KBS in Marine Collision Avoidance
Coenen, F., & Smeaton, P. (1991). KBS in Marine Collision Avoidance. In Applications of Artificial Intelligence in Engineering VI (pp. 529-539). Springer Netherlands. doi:10.1007/978-94-011-3648-8_34
Rule-based algorithms for geographic constraints in a marine knowledge-based system
Coenen, F., & Smeaton, P. (1991). Rule-based algorithms for geographic constraints in a marine knowledge-based system. Knowledge-Based Systems, 4(3), 157-164. doi:10.1016/0950-7051(91)90004-l
1990
Developing an intelligent marine navigation system
Smeaton, G. P., & Coenen, F. P. (1990). Developing an intelligent marine navigation system. Computing & Control Engineering Journal, 1(2), 95. doi:10.1049/cce:19900024
1989
Knowledge-based Collision Avoidance
Coenen, F. P., Smeaton, G. P., & Bole, A. G. (1989). Knowledge-based Collision Avoidance. Journal of Navigation, 42(1), 107-116. doi:10.1017/s0373463300015125