List of publications. See also Google Scholar Profile.

  • S. Datta, D. Ganguly, S. MacAvaney and D. Greene, “A Deep Learning approach for Selective Relevance Feedback,” in Proc. European Conference on Information Retrieval (ECIR'24), 2024. [PDF] [BibTeX] [Link]

  • D. Greene, J. O'Sullivan, and D. O'Reilly, “Topic modelling literary interviews from The Paris Review,” in Digital Scholarship in the Humanities, 2024. [PDF] [BibTeX] [Link]

  • E. Delaney, A. Pakrashi, D. Greene, and M.T. Keane, “Counterfactual Explanations for Misclassified Images: How Human and Machine Explanations Differ,” in Artificial Intelligence, 2023. [PDF] [BibTeX] [Link]

  • J.P. Cross, D. Greene, N. Umansky and S. Calò “Speaking in unison? Explaining the role of agenda-setter constellations in the ECB policy agenda using a network-based approach,” Journal of European Public Policy, Taylor & Francis, 2023. [PDF] [BibTeX] [Link]

  • E. Cunningham and D. Greene, “Surrogate explanations for role discovery on graphs,” Applied Network Science, 2023. [PDF] [BibTeX] [Link]

  • S. Sawant, S. Thakare, D. Greene, G. Meaney, and A. Smeaton, “Handwriting Analysis on the Diaries of Rosamond Jacob,” in Proc. 20th International Conference on Content-based Multimedia Indexing (CBMI'23), 2023. [PDF] [BibTeX] [Link]

  • N. O'Shea, D. Greene, and M. Fenelon, “Artificial Intelligence in Food Safety,” Encyclopedia of Food Safety (Second Edition), 2023. [BibTeX] [Link]

  • E. Delaney, A. Pakrashi, D. Greene, and M.T. Keane, “Counterfactual explanations for misclassified images: How human and machine explanations differ,” in ICML-23 Workshop on Counterfactuals in Minds and Machines, 2023. [PDF] [BibTeX]

  • E. Cunningham and D. Greene, “Graph Embedding for Mapping Interdisciplinary Research Networks,” in Companion Proc. the Web Conference WWW'23, 2023. [PDF] [BibTeX] [Link]

  • S. Datta, D. Ganguly, D. Greene, and M. Mitra, “On the Feasibility and Robustness of Pointwise Evaluation of Query Performance Prediction,” in Proc. Workshop on Query Performance Prediction and its Evaluation in New Tasks (QPP++) at ECIR'23, 2023. [PDF] [BibTeX]

  • E. Delaney, E. Kenny, D. Greene, and M.T. Keane, “User tests & techniques for the post-hoc explainability of deep learning models,” in Explainable Deep Learning AI: Methods and Challenges, Academic Press, 2023. [PDF] [BibTeX] [Link]

  • E. Hayes, D. Wallace, C. O'Donnell, D. Greene, D. Hennessy, N. O'Shea, J. Tobin, and M. Fenelon, “Trend analysis and prediction of seasonal changes in milk composition from a pasture-based dairy research herd,” Journal of Dairy Science, 2023. [PDF] [BibTeX] [Link]

  • E. Hayes, D. Greene, C. O'Donnell, N. O'Shea, and M. Fenelon, “Spectroscopic technologies and data fusion: Applications for the dairy industry,” Frontiers in Nutrition, 2023. [PDF] [BibTeX] [Link]

  • E. Cunningham, B. Smyth, and D. Greene, “Author multidisciplinarity and disciplinary roles in field of study networks,” Applied Network Science, 2022. [PDF] [BibTeX] [Link]

  • S. Sadler, D. Greene, and D. Archambault, “Towards explainable community finding,” Applied Network Science, 2022. [PDF] [BibTeX] [Link]

  • S. Datta, D. Ganguly, M. Mitra, and D. Greene, “A Relative Information Gain-based Query Performance Prediction Framework with Generated Query Variants,” Transactions on Information Systems, ACM, 2022. [PDF] [BibTeX] [Link]

  • E. Cunningham and D. Greene, “The Structure of Interdisciplinary Science: Uncovering and Explaining Roles in Citation Graphs,” in Proc. 11th International Conference on Complex Networks and Their Applications, 2022. [PDF] [BibTeX]

  • E. Delaney, D. Greene, L. Shalloo, M. Lynch, and M.T. Keane, “Forecasting for sustainable dairy produce: Enhanced long-term, milk-supply forecasting using k-NN for data augmentation, with prefactual explanations for XAI,” in Proc. 30th International Conference on Case-Based Reasoning (ICCBR-2022), 2022. [PDF] [BibTeX] [Link]

  • S. Datta, S. MacAvaney, D. Ganguly, and D. Greene, “A ‘Pointwise-Query, Listwise-Document’ Based Query Performance Prediction Approach,” in Proc. the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR’22), 2022. [PDF] [BibTeX] [Link]

  • P. Leydon, M. O’Connell, D. Greene, and K. Curran, “Bone segmentation in contrast enhanced whole-body computed tomography,” Biomedical Physics & Engineering Express, IOP Publishing, 2022. [PDF] [BibTeX] [Link]

  • E. Cunningham and D. Greene, “Assessing Network Representations for Identifying Interdisciplinarity,” in Companion Proc. the Web Conference WWW'22, 2022. [PDF] [BibTeX] [Link]

  • D. Liu, D. Greene, and R. Dong, “A novel perspective to look at attention: Bi-level attention-based explainable topic modeling for news classification,” in Findings of the Association for Computational Linguistics: ACL 2022, 2022. [PDF] [BibTeX] [Link]

  • D. Ganguly, S. Datta, M. Mitra, and D. Greene, “An Analysis of Variations in the Effectiveness of Query Performance Prediction,” in Proc. 44th European Conference on Information Retrieval (ECIR’22), 2022. [PDF] [BibTeX] [Link]

  • S. Datta, D. Ganguly, D. Greene, and M. Mitra, “Deep-QPP: A Pairwise Interaction-based Deep Learning Model for Supervised Query Performance Prediction,” in Proc. 15th International Conference on Web Search and Data Mining (WSDM’22), 2022. [PDF] [BibTeX] [Link]

  • E. Cunningham, B. Smyth, and D. Greene, “Collaboration in the Time of COVID: A Scientometric Analysis of Multidisciplinary SARS-CoV-2 Research,” Humanities and Social Sciences Communications, Springer Nature, 2021. [PDF] [BibTeX] [Link]

  • D. Wallace, E. Delaney, M.T. Keane, and D. Greene, “Nearest Neighbour-Based Data Augmentation for Time Series Forecasting,” in Proc. 29th Irish Conference on Artificial Intelligence and Cognitive Science (AICS’21), 2021. [BibTeX]

  • E. Delaney, D. Greene, and M.T. Keane, “Instance-based Counterfactual Explanations for Time Series Classification,” in Proc. 29th International Conference on Case-Based Reasoning (ICCBR-2021), 2021. [PDF] [BibTeX] [Link]

  • S. Sadler, D. Greene, and D. Archambault, “Selecting Informative Features for Post-Hoc Community Explanation,” in Proc. 10th International Conference on Complex Networks and Their Applications, 2021. [PDF] [BibTeX] [Link]

  • E. Cunningham, B. Smyth, and D. Greene, “Navigating Multidisciplinary Research Using Field of Study Networks,” in Proc. 10th International Conference on Complex Networks and Their Applications, 2021. [PDF] [BibTeX] [Link]

  • E. Delaney, D. Greene, and M.T. Keane, “Uncertainty Estimation and Out-of-Distribution Detection for Counterfactual Explanations: Pitfalls and Solutions,” in ICML-21 Workshop on Algorithmic Recourse, 2021. [PDF] [BibTeX]

  • M.T. Keane, E. Kenny, M. Temraz, D. Greene, and B. Smyth, “Twin Systems for DeepCBR: A Menagerie of Deep Learning and Case-Based Reasoning Pairings for Explanation and Data Augmentation,” in IJCAI-21 Workshop on Deep Learning, Case-Based Reasoning, and AutoML, 2021. [PDF] [BibTeX]

  • E. Kenny, E. Delaney, D. Greene, and M.T. Keane, “Post-hoc Explanation Options for XAI in Deep Learning,” in Proc. International Conference on Pattern Recognition International Workshops and Challenges (ICPR’21), 2021. [PDF] [BibTeX] [Link]

  • F. Marshall and others, “Development of the Ground Segment Communication System for the EIRSAT-1 CubeSat,” in 16th International Conference on Space Operations (SpaceOps-2021), 2021. [PDF] [BibTeX]

  • S. Datta, D. Ganguly, D. Roy, D. Greene, C. Jochim, and F. Bonin, “Overview of the Causality-Driven Adhoc Information Retrieval (CAIR) Task at FIRE-2020,” in Forum for Information Retrieval Evaluation, 2020. [PDF] [BibTeX] [Link]

  • E. Alghamdi, E. Rushe, B. Mac Namee, and D. Greene, “Overlapping Community Finding with Noisy Pairwise Constraints,” Applied Network Science, Springer, 2020. [PDF] [BibTeX] [Link]

  • S. Datta, D. Greene, D. Ganguly, D. Roy, and M. Mitra, “Where’s the Why? In Search of Chains of Causes for Query Events,” in Proc. 28th Irish Conference on Artificial Intelligence and Cognitive Science (AICS’20), 2020. [PDF] [BibTeX]

  • E. Cunningham and D. Greene, “Active Learning for the Text Classification of Rock Climbing Logbook Data,” in Proc. 28th Irish Conference on Artificial Intelligence and Cognitive Science (AICS’20), 2020. [PDF] [BibTeX]

  • G. Meaney, D. Greene, K. Wade, and M. Mulvany, “The Woman Between: A Social Network Analysis of The Fall and The Bridge,” in Noir in the North: Genre, Politics and Place, Bloomsbury, 2020. [BibTeX] [Link]

  • M. Belford and D. Greene, “Ensemble Topic Modeling using Weighted Term Co-associations,” Expert Systems with Applications, Elsevier, 2020. [PDF] [BibTeX] [Link]

  • S. Leavy, G. Meaney, K. Wade, and D. Greene, “Mitigating Gender Bias in Machine Learning Data Sets,” in Bias and Social Aspects in Search and Recommendation (Bias 2020), 2020. [BibTeX] [Link]

  • E. Alghamdi, E. Rushe, M. Bazargani, B. Mac Namee, and D. Greene, “Handling Noisy Constraints in Semi-supervised Overlapping Community Finding,” in Proc. 8th International Conference on Complex Networks and Their Applications, 2019. [PDF] [BibTeX]

  • P. Leydon, M. O’Connell, D. Greene, and K. Curran, “Cross-Correlation Template Matching for Liver Localisation in Computed Tomography,” in Proc. Irish Machine Vision and Image Processing Conference (IMVIP 2019), 2019. [BibTeX]

  • P. Leydon, M. O’Connell, D. Greene, and K. Curran, “Synthetic Positron Emission Tomography Using Conditional-Generative Adversarial Networks for Healthy Bone Marrow Baseline Image Generation,” in Proc. Irish Machine Vision and Image Processing Conference (IMVIP 2019), 2019. [BibTeX]

  • E. Alghamdi and D. Greene, “Active Semi-Supervised Overlapping Community Finding with Pairwise Constraints,” Applied Network Science, Springer, 2019. [PDF] [BibTeX] [Link]

  • J.P. Cross and D. Greene, “Talk is not cheap: Policy agendas, information processing, and the unusually proportional nature of ECB communications policy responses,” Governance, Wiley, 2019. [PDF] [BibTeX] [Link]

  • S. Leavy, G. Meaney, K. Wade, and D. Greene, “Curatr: A Platform for Semantic Analysis and Curation of Historical Literary Texts,” in Proc. 13th International Conference on Metadata and Semantics Research (MTSR 2019), 2019. [BibTeX]

  • M. Belford and D. Greene, “A Comparison of Word Embedding Techniques for Measuring Topic Model Coherence,” in Proc. 2nd International Conference on Language, Data and Knowledge (LDK’2019), 2019. [PDF] [BibTeX]

  • D. Greene, B. Bringmann, E. Fromont, and J. Davis, “Introduction to the special issue for the ECML PKDD 2018 journal track,” Data Mining and Knowledge Discovery, 2018. [BibTeX] [Link]

  • J. Davis, B. Bringmann, E. Fromont, and D. Greene, “Guest editors introduction to the special issue for the ECML PKDD 2018 journal track,” Machine Learning, 2018. [BibTeX] [Link]

  • E. Alghamdi and D. Greene, “Semi-Supervised Overlapping Community Finding based on Label Propagation with Pairwise Constraints,” in Proc. 7th International Conference on Complex Networks and Their Applications, 2018. [PDF] [BibTeX]

  • S. Grayson and D. Greene, “Temporal alignment of Reddit network embeddings,” in Proc. 7th International Conference on Complex Networks and Their Applications, 2018. [BibTeX]

  • S. Grayson and D. Greene, “Temporal analysis of Reddit networks via role embeddings,” in Proc. 14th International Workshop on Mining and Learning with Graphs, at KDD’18, 2018. [PDF] [BibTeX]

  • M. Qureshi and D. Greene, “EVE: Explainable vector based embedding technique using Wikipedia,” Journal of Intelligent Information Systems, 2018. [PDF] [BibTeX] [Link]

  • J. Suiter, E. Culloty, D. Greene, and E. Siapera, “Hybrid Media and Populist Currents in Ireland’s 2016 General Election,” European Journal of Communication, 2018. [BibTeX] [Link]

  • S. Leavy, K. Wade, G. Meaney, and D. Greene, “Navigating Literary Text Using Word Embeddings and Semantic Lexicons,” in Proc. Workshop on Computational Methods in the Humanities (COMHUM 2018), 2018. [PDF] [BibTeX]

  • M. Belford, B. Mac Namee, and D. Greene, “Stability of topic modeling via matrix factorization,” Expert Systems with Applications, 2018. [PDF] [BibTeX] [Link]

  • P. Leydon, M. O’Connell, D. Greene, and K. Curran, “Semi-automatic Bone Marrow Evaluation in PETCT for Multiple Myeloma,” in Annual Conference on Medical Image Understanding and Analysis, 2017. [BibTeX]

  • C. Orellana-Rodriguez, D. Greene, and M.T. Keane, “Spreading One’s Tweets: How Can Journalists Gain Attention for their Tweeted News?,” The Journal of Web Science, 2017. [PDF] [BibTeX] [Link]

  • M. Qureshi and D. Greene, “Lit@EVE: Explainable Recommendation based on Wikipedia Concept Vectors,” in Proc. European Conference on Machine Learning (ECML’17), 2017. [PDF] [BibTeX]

  • G. Conheady and D. Greene, “Weak Supervision for Semi-Supervised Topic Modeling via Word Embeddings,” in Proc. 1st International Conference on Language, Data and Knowledge (LDK’2017), 2017. [PDF] [BibTeX] [Link]

  • S. Grayson, M. Mulvany, K. Wade, G. Meaney, and D. Greene, “Exploring the Role of Gender in 19th Century Fiction Through the Lens of Word Embeddings,” in Language, Data, and Knowledge: First International Conference (LDK’2017), 2017. [PDF] [BibTeX]

  • D. Greene and J.P. Cross, “Exploring the Political Agenda of the European Parliament Using a Dynamic Topic Modeling Approach,” Political Analysis, 2017. [PDF] [BibTeX] [Link]

  • M. Qureshi, A. Younus, and D. Greene, “TwitterCracy: Exploratory Monitoring of Twitter Streams for the 2016 U.S. Presidential Election Cycle,” in Proc. European Conference on Machine Learning (ECML’16), 2016. [PDF] [BibTeX]

  • S. Grayson, K. Wade, G. Meaney, and D. Greene, “The Sense and Sensibility of Different Sliding Windows in Constructing Co-occurrence Networks from Literature,” in Proc. 2nd International Workshop on Computational History and Data-Driven Humanities, 2016. [PDF] [BibTeX]

  • S. Grayson, J. Rothwell, M. Mulvany, K. Wade, G. Meaney, and D. Greene, “Discovering Structure in Social Networks of 19th Century Fiction,” in Proc. the 8th ACM Conference on Web Science, 2016. [PDF] [BibTeX] [Link]

  • J. Su, D. Greene, and O. Boydell, “Topic Stability over Noisy Sources,” in Proc. the 2nd Workshop on Noisy User-generated Text (WNUT), 2016. [PDF] [BibTeX]

  • C. Orellana-Rodriguez, D. Greene, and M.T. Keane, “Spreading the News: How Can Journalists Gain More Engagement for Their Tweets?,” in Proc. ACM Web Science 2016, 2016. [PDF] [BibTeX] [Link]

  • I. Brigadir, D. Greene, and P. Cunningham, “Detecting Attention Dominating Moments Across Media Types,” in Proc. 1st International Workshop on Recent Trends in News Information Retrieval (NewsIR’16) at ECIR’16, 2016. [PDF] [BibTeX]

  • X. Qin, D. Greene, and P. Cunningham, “A Latent Space Analysis of Editor Lifecycles in Wikipedia,” in Big Data Analytics in the Social and Ubiquitous Context, Springer, 2016. [PDF] [BibTeX]

  • P. Leydon, F. Sullivan, F. Jamaluddin, P. Woulfe, D. Greene, and K. Curran, “Machine Learning in Prediction of Prostate Brachytherapy Rectal Dose Classes at Day 30,” in Proc. 17th Irish Machine Vision and Image Processing conference, 2015. [PDF] [BibTeX]

  • I. Brigadir, D. Greene, and P. Cunningham, “Analyzing Discourse Communities with Distributional Semantic Models,” in Proc. ACM Web Science 2015, 2015. [PDF] [BibTeX] [Link]

  • D. Greene and J.P. Cross, “Unveiling the Political Agenda of the European Parliament Plenary: A Topical Analysis,” in Proc. ACM Web Science 2015, 2015. [PDF] [BibTeX] [Link]

  • D. O’Callaghan, D. Greene, J. Carthy, and P. Cunningham, “An Analysis of the Coherence of Descriptors in Topic Modeling,” Expert Systems with Applications, Elsevier, 2015. [PDF] [BibTeX]

  • D. Fitzpatrick, C. Ryan, N. Shah, D. Greene, C. Molony, and D. Shields, “Genome-wide epistatic expression quantitative trait loci discovery in four human tissues reveals the importance of local chromosomal interactions governing gene expression,” BMC Genomics, BioMed Central, 2015. [PDF] [BibTeX]

  • D. O’Callaghan, D. Greene, M. Conway, J. Carthy, and P. Cunningham, “Down the (White) Rabbit Hole: The Extreme Right and Online Recommender Systems,” Social Science Computer Review, 2014. [PDF] [BibTeX] [Link]

  • I. Brigadir, D. Greene, and P. Cunningham, “Adaptive Representations for Tracking Breaking News on Twitter,” in NewsKDD - Workshop on Data Science for News Publishing at KDD 2014, 2014. [PDF] [BibTeX]

  • D. Greene, D. O’Callaghan, and P. Cunningham, “How Many Topics? Stability Analysis for Topic Models,” in Proc. European Conference on Machine Learning (ECML’14), 2014. [PDF] [BibTeX]

  • D. O’Callaghan, N. Prucha, D. Greene, M. Conway, J. Carthy, and P. Cunningham, “Online Social Media in the Syria Conflict: Encompassing the Extremes and the In-Betweens,” in Proc. International Conference on Advances in Social Networks Analysis and Mining (ASONAM’14), 2014. [PDF] [BibTeX]

  • I. Brigadir, D. Greene, P. Cunningham, and G. Sheridan, “Real Time Event Monitoring with Trident,” in Proc. Workshop on Real-World Challenges for Data Stream Mining (RealStream) at ECML 2013, 2013. [PDF] [BibTeX]

  • I. Hulpus, C. Hayes, M. Karnstedt, D. Greene, and M. Jozwowicz, “Kanopy: Analysing the Semantic Network around Document Topics,” in Proc. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD’13), 2013. [PDF] [BibTeX]

  • D. O’Callaghan, D. Greene, M. Conway, J. Carthy, and P. Cunningham, “Uncovering the Wider Structure of Extreme Right Communities Spanning Popular Online Networks,” in Proc. ACM Web Science 2013, 2013. [PDF] [BibTeX]

  • D. Greene and P. Cunningham, “Producing a Unified Graph Representation from Multiple Social Network Views,” in Proc. ACM Web Science 2013, 2013. [PDF] [BibTeX]

  • I. Hulpus, C. Hayes, M. Karnstedt, and D. Greene, “Unsupervised Graph-Based Topic Labelling using DBpedia,” in Proc. 6th ACM International Conference on Web Search and Data Mining (WSDM’13), 2013. [PDF] [BibTeX]

  • I. Hulpus, C. Hayes, M. Karnstedt, and D. Greene, “An Eigenvalue-Based Measure for Word-Sense Disambiguation,” in Proc. Twenty-Fifth International FLAIRS Conference, 2012. [PDF] [BibTeX]

  • I. Brigadir, D. Greene, and P. Cunningham, “A System for Twitter User List Curation,” in Proc. 6th ACM Conference on Recommender Systems (RecSys’12), 2012. [PDF] [BibTeX]

  • S. Delany, M. Buckley, and D. Greene, “SMS Spam Filtering,” Expert Systems with Applications, Pergamon Press, Inc., 2012. [PDF] [BibTeX] [Link]

  • D. Greene, D. O’Callaghan, and P. Cunningham, “Identifying Topical Twitter Communities via User List Aggregation,” in Proc. 2nd International Workshop on Mining Communities and People Recommenders (COMMPER 2012) at ECML 2012, 2012. [PDF] [BibTeX]

  • D. Greene, G. Sheridan, B. Smyth, and P. Cunningham, “Aggregating Content and Network Information to Curate Twitter User Lists,” in Proc. 4th ACM RecSys Workshop on Recommender Systems & The Social Web, 2012. [PDF] [BibTeX]

  • D. O’Callaghan, D. Greene, M. Conway, J. Carthy, and P. Cunningham, “An Analysis of Interactions Within and Between Extreme Right Communities in Social Media,” in Proc. 3rd International Workshop on Mining Ubiquitous and Social Environments (MUSE) at ECML 2012, 2012. [PDF] [BibTeX]

  • C. Ryan and others, “Hierarchical Modularity and the Evolution of Genetic Interactomes across Species,” Molecular Cell, 2012. [PDF] [BibTeX]

  • A. McDaid, D. Greene, and N. Hurley, “Normalized Mutual Information to evaluate overlapping community finding algorithms,” ArXiv e-prints, 2011. [PDF] [BibTeX]

  • D. Archambault, D. Greene, P. Cunningham, and N. Hurley, “ThemeCrowds: Multiresolution Summaries of Twitter Usage,” in Proc. 3rd International Workshop on Search and Mining User-generated Content (SMUC’11), 2011. [PDF] [BibTeX]

  • A. Brew, D. Greene, D. Archambault, and P. Cunningham, “Deriving Insights from National Happiness Indices,” in Proc. ICDM 2011 Workshop on Sentiment Elicitation from Natural Text for Information Retrieval and Extraction (SENTIRE), 2011. [PDF] [BibTeX]

  • D. Greene, F. Reid, G. Sheridan, and P. Cunningham, “Supporting the Curation of Twitter User Lists,” in 2nd Workshop on Computational Social Science and the Wisdom of Crowds at NIPS 2011, 2011. [PDF] [BibTeX]

  • C. Lee, D. Greene, and P. Cunningham, “Detecting Grand Tours of Europe with Geo-Tags,” in 2nd Workshop on Computational Social Science and the Wisdom of Crowds at NIPS 2011, 2011. [PDF] [BibTeX]

  • C. Ryan, G. Cagney, N. Krogan, P. Cunningham, and D. Greene, “Imputing and Predicting Quantitative Genetic Interactions in Epistatic MAPs,” in Network Biology, Methods in Molecular Biology, Humana Press, 2011. [PDF] [BibTeX]

  • C. Ryan, D. Greene, G. Cagney, A. Guenole, H. Attikum, N. Krogan, and P. Cunningham, “Improved functional overview of protein complexes using inferred epistatic relationships,” BMC Systems Biology, 2011. [PDF] [BibTeX]

  • K. Wade, D. Greene, C. Lee, D. Archambault, and P. Cunningham, “Identifying Representative Textual Sources in Blog Networks,” in Proc. 5th International AAAI Conference on Weblogs and Social Media (ICWSM’11), 2011. [PDF] [BibTeX]

  • A. Brew, D. Greene, and P. Cunningham, “The interaction between supervised learning and crowdsourcing,” in NIPS Workshop on Computational Social Science and the Wisdom of Crowds, 2010. [PDF] [BibTeX]

  • A. Brew, D. Greene, and P. Cunningham, “Using Crowdsourcing and Active Learning to Track Sentiment in Online Media,” in Proc. 19th European Conference on Artificial Intelligence (ECAI 2010), 2010. [PDF] [BibTeX]

  • A. Brew, D. Greene, and P. Cunningham, “Taking the Pulse of the Web: Assessing Sentiment on Topics in Online Media,” in Proc. WebSci10: Extending the Frontiers of Society On-Line, 2010. [PDF] [BibTeX]

  • D. Greene, J. Freyne, B. Smyth, and P. Cunningham, “An Analysis of Current Trends in CBR Research Using Multi-View Clustering,” AI Magazine, 2010. [PDF] [BibTeX]

  • D. Greene and P. Cunningham, “Spectral Co-Clustering for Dynamic Bipartite Graphs,” in Workshop on Dynamic Networks and Knowledge Discovery (DyNAK’10), 2010. [PDF] [BibTeX]

  • D. Greene, D. Doyle, and P. Cunningham, “Tracking the evolution of communities in dynamic social networks,” in Proc. International Conference on Advances in Social Networks Analysis and Mining (ASONAM’10), 2010. [PDF] [BibTeX]

  • C. Ryan, D. Greene, G. Cagney, and P. Cunningham, “Missing value imputation for epistatic MAPs,” BMC Bioinformatics, 2010. [PDF] [BibTeX]

  • G. Wu, D. Greene, and P. Cunningham, “Merging Multiple Criteria to Identify Suspicious Reviews,” in Proc. 4th ACM Conference on Recommender Systems (RecSys’10), 2010. [PDF] [BibTeX]

  • G. Wu, D. Greene, B. Smyth, and P. Cunningham, “Distortion as a Validation Criterion in the Identification of Suspicious Reviews,” in 1st Workshop on Social Media Analytics (SOMA’10), 2010. [PDF] [BibTeX]

  • A. Narasimhamurthy, D. Greene, N. Hurley, and P. Cunningham, “Partitioning Large Networks Without Breaking Communities,” Knowledge and Information Systems, 2009. [PDF] [BibTeX]

  • D. Greene and P. Cunningham, “Multi-view clustering for mining heterogeneous social network data,” in Workshop on Information Retrieval over Social Networks, 31st European Conference on Information Retrieval (ECIR’09), 2009. [PDF] [BibTeX]

  • D. Greene and P. Cunningham, “A Matrix Factorization Approach for Integrating Multiple Data Views,” in Proc. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD’09), 2009. [PDF] [BibTeX]

  • D. Greene, K. Bryan, and P. Cunningham, “Parallel Integration of Heterogeneous Genome-Wide Data Sources,” in Proc. 8th International Conference on BioInformatics and BioEngineering (BIBE’08), 2008. [PDF] [BibTeX]

  • D. Greene, J. Freyne, B. Smyth, and P. Cunningham, “An Analysis of Research Themes in the CBR Conference Literature,” in Proc. 9th European Conference on Case-Based Reasoning (ECCBR’08), 2008. [PDF] [BibTeX]

  • D. Greene, P. Cunningham, and R. Mayer, “Unsupervised Learning and Clustering,” in Machine Learning Techniques for Multimedia: Case Studies on Organization and Retrieval, Springer, 2008. [PDF] [BibTeX]

  • D. Greene, G. Cagney, N. Krogan, and P. Cunningham, “Ensemble Non-negative Matrix Factorization Methods for Clustering Protein-Protein Interactions,” Bioinformatics, 2008. [PDF] [BibTeX]

  • D. Greene and P. Cunningham, “Constraint Selection by Committee: An Ensemble Approach to Identifying Informative Constraints for Semi-Supervised Clustering,” in Proc. 18th European Conference on Machine Learning (ECML’07), 2007. [PDF] [BibTeX]

  • D. Greene and P. Cunningham, “Efficient Prediction-Based Validation for Document Clustering,” in Proc. 17th European Conference on Machine Learning (ECML’06), 2006. [PDF] [BibTeX]

  • D. Greene and P. Cunningham, “Practical Solutions to the Problem of Diagonal Dominance in Kernel Document Clustering,” in Proc. 23rd International Conference on Machine learning (ICML’06), 2006. [PDF] [BibTeX]

  • D. Greene and P. Cunningham, “Producing Accurate Interpretable Clusters from High-Dimensional Data,” in Proc. 9th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD’05), 2005. [PDF] [BibTeX]

  • D. Greene, A. Tsymbal, N. Bolshakova, and P. Cunningham, “Ensemble Clustering in Medical Diagnostics,” in Proc. 17th IEEE Symposium on Computer-Based Medical Systems (CBMS’04), 2004. [PDF] [BibTeX]

  • D. Greene and D. O’Mahony, “Instant Messaging and Presence Management in Mobile Ad-Hoc Networks,” in Proc. 2nd IEEE Annual Conference on Pervasive Computing and Communications Workshops (PERCOMW’04), 2004. [PDF] [BibTeX]