Publications

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Islamaj, R., Getoor, L. & W. Wilbur, J. Feature Generation Algorithm: an Application to Splice Site Prediction. Knowledge Discovery in Databases: PKDD 2006 4213, 553-560 (Springer, 2006).PDF icon rezarta-pkdd.pdf (163.92 KB)
Islamaj, R., Getoor, L. & W. Wilbur, J. A Feature Generation Algorithm for Sequences with Application to Splice Site Prediction. International Workshop on Feature Selection for Data Mining (FSDM) (2006).
Islamaj, R., Getoor, L., W. Wilbur, J. & Mount, S. Features generated for computational splice-site prediction correspond to functional elements. BMC Bioinformatics 8, (2007).
Sharara, H., Singh, L. & Getoor, L. Finding Prominent Actors in Dynamic Affiliation Networks. Human Journal (2012).PDF icon 105-204-1-SM.pdf (757.7 KB)
Rekatsinas, T., Dong, X. Luna, Getoor, L. & Srivastava, D. Finding Quality in Quantity: The Challenge of Discovering Valuable Sources for Integration. 7th Biennial Conference on Innovative Data Systems Research (CIDR `15) (2015).PDF icon rekatsinasCIDR15.pdf (396.99 KB)
Rekatsinas, T. et al. Forecasting Rare Disease Outbreaks Using Multiple Data Sources. STAT ANAL DATA MIN (2015).
Getoor, L., Koller, D. & Friedman, N. From Instances to Classes in Probabilistic Relational Models. Proceedings of the ICML Workshop on Attribute-Value and Relational Learning: Crossing the Boundaries (2000).
Getoor, L., Koller, D. & Friedman, N. From Instances to Classes in Probabilistic Relational Models. Proceedings of the ICML Workshop on Attribute-Value and Relational Learning: Crossing the Boundaries (2000).
Sayyadi, H. & Getoor, L. Future Rank: Ranking Scientific Articles by Predicting their Future PageRank. 2009 SIAM International Conference on Data Mining (SDM09) (2009).PDF icon sayyadi_futureRank_sdm09.pdf (621.55 KB)
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Sharara, H., Sopan, A., Namata, G. Mark, Getoor, L. & Singh, L. G-PARE: A Visual Analytic Tool for Comparative Analysis of Uncertain Graphs. IEEE Conference on Visual Analytics Science and Technology (VAST) (2011).PDF icon sharara-vast11.pdf (1.64 MB)
Pujara, J. & Getoor, L. Generic Statistical Relational Entity Resolution in Knowledge Graphs. StarAI (IJCAI 2016, 2016). doi:2016PDF icon pujara-starai16.pdf (151.37 KB)
Kang, H., Sehgal, V. & Getoor, L. GeoDDupe: A Novel Interface for Interactive Entity Resolution in Geospatial Data. International Conference on Information Visualization (IEEE Computer Society, 2007).PDF icon kangiv07.pdf (1.34 MB)
Moustafa, W., Miao, H., Deshpande, A. & Getoor, L. GrDB: A System for Declarative and Interactive Analysis of Noisy Information Networks. SIGMOD (2013).PDF icon moustafa-sigmod13.pdf (1.1 MB)
Memory, A., Kimmig, A., Bach, S. H., Raschid, L. & Getoor, L. Graph Summarization in Annotated Data Using Probabilistic Soft Logic. Proceedings of the International Workshop on Uncertainty Reasoning for the Semantic Web (URSW) (2012).PDF icon mrc_iswc12_ws.pdf (411.71 KB)
Haidarian-Shahri, H., Namata, G. Mark, Navlakha, S., Deshpande, A. & Roussopoulos, N. A Graph-based Approach to Vehicle Tracking in Traffic Camera Video Streams. 4th International Workshop on Data Management for Sensor Networks (2007).PDF icon dmsn07.pdf (576.07 KB)
London, B., Huang, B. & Getoor, L. Graph-based Generalization Bounds for Learning Binary Relations. (2013).PDF icon br_risk_bounds.pdf (304.54 KB)
Deshpande, A., Getoor, L. & Sen, P. Graphical Models for Uncertain Data. Managing and Mining Uncertain Data 1, 1--34 (Springer, 2009).PDF icon deshpande-book09.pdf (570.7 KB)
Koller, D., Friedman, N., Getoor, L. & Taskar, B. Graphical Models in a Nutshell. An Introduction to Statistical Relational Learning 1, 13--55 (MIT Press, 2007).PDF icon koller-book07.pdf (513.11 KB)
Sharara, H. & Getoor, L. Group Detection. Encyclopedia of Machine Learning (2010).
Saha, B. & Getoor, L. Group Proximity Measure for Recommending Groups in Online Social Networks. 2nd ACM SIGKDD Workshop on Social Network Mining and Analysis (SNA-KDD) (2008).PDF icon kddw-saha.pdf (311.36 KB)
Plangprasopchok, A., Lerman, K. & Getoor, L. Growing a tree in the forest: constructing folksonomies by integrating structured metadata. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2010).PDF icon plang-kdd10.pdf (705.71 KB)
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Udrea, O., Getoor, L. & Miller, R. HOMER: Ontology Alignment Visualization and Analysis. (2007).PDF icon getoor-homer07.pdf (125.38 KB)
Udrea, O., Miller, R. & Getoor, L. HOMER: Ontology visualization and analysis. Demo Presentation at International Semantic Web Conference (ISWC) (2007).PDF icon homer.pdf (125.38 KB)
He, X., Rekatsinas, T., Foulds, J., Getoor, L. & Liu, Y. HawkesTopic: A Joint Model for Network Inference and Topic Modeling from Text-Based Cascades. International Conference on Machine Learning (2015).PDF icon He2015HawkesTopic.pdf (819.91 KB)
Zheleva, E., Getoor, L. & Sarawagi, S. Higher-order Graphical Models for Classification in Social and Affiliation Networks. NIPS Workshop on Networks Across Disciplines: Theory and Applications (2010).PDF icon zheleva-nips2010.pdf (200.43 KB)
Bach, S. H., Broecheler, M., Huang, B. & Getoor, L. Hinge-Loss Markov Random Fields and Probabilistic Soft Logic. Journal of Machine Learning Research (JMLR) 18, 1-67 (2017).PDF icon bach-jmlr17.pdf (731.56 KB)
Bach, S. H., Broecheler, M., Huang, B. & Getoor, L. Hinge-Loss Markov Random Fields and Probabilistic Soft Logic. ArXiv:1505.04406 [cs.LG] (2015).PDF icon bach-arxiv15.pdf (686.27 KB)
Bach, S. H. Hinge-Loss Markov Random Fields and Probabilistic Soft Logic: A Scalable Approach to Structured Prediction. (2015).PDF icon bach-thesis15.pdf (1.17 MB)
Bach, S. H., Huang, B., London, B. & Getoor, L. Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction. Uncertainty in Artificial Intelligence (2013).PDF icon bach-uai13.pdf (379.45 KB)
Kouki, P., Fakhraei, S., Foulds, J., Eirinaki, M. & Getoor, L. HyPER: A Flexible and Extensible Probabilistic Framework for Hybrid Recommender Systems. 9th ACM Conference on Recommender Systems (RecSys) (ACM, 2015).PDF icon kouki-recsys15.pdf (1.03 MB)
Miao, H., Liu, X., Huang, B. & Getoor, L. A Hypergraph-Partitioned Vertex Programming Approach for Large-scale Consensus Optimization. 2013 IEEE International Conference on Big Data (2013).PDF icon miao-bd13.pdf (307.51 KB)
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Srinivasan, S., Rao, N. S., Subbaian, K. & Getoor, L. Identifying Facet Mismatches In Search Via Micrographs. CIKM (2019).PDF icon srinivasan-cikm19.pdf (887.06 KB)
Namata, G. Mark & Getoor, L. Identifying Graphs From Noisy and Incomplete Data. 1st ACM SIGKDD Workshop on Knowledge Discovery from Uncertain Data (2009).PDF icon namatag-kddu09.pdf (241.7 KB)
Namata, G. Mark. Identifying Graphs from Noisy Observational Data. (2012).PDF icon namata-phdthesis.pdf (1.51 MB)
Tomkins, S., Farnadi, G., Amantullah, B., Getoor, L. & Minton, S. The Impact of Environmental Stressors on Human Trafficking. Beyond Online Data (ICWSM Workshop) (2018).PDF icon icdm_2018.pdf (473.58 KB)
Tomkins, S., Farnadi, G., Amantullah, B., Getoor, L. & Minton, S. The Impact of Environmental Stressors on Human Trafficking. International Conference on Data Mining (ICDM) (2018).PDF icon icdm_2018.pdf (473.58 KB)
London, B., Huang, B. & Getoor, L. Improved Generalization Bounds for Large-scale Structured Prediction. NIPS Workshop on Algorithmic and Statistical Approaches for Large Social Networks (2012).PDF icon london-nips12ws.pdf (213.95 KB)
Minton, S. et al. Improving Classifier Performance by Autonomously Collecting Background Knowledge from the Web. Tenth International Conference on Machine Learning and Applications (2011).PDF icon minton-icmla2011.pdf (733.09 KB)
Singh, L. & Getoor, L. Increasing the predictive power of affiliation networks. IEEE Data Engineering Bulletin 30, (2007).PDF icon singh.pdf (87.94 KB)
Schnaitter, K., Polyzotis, N. & Getoor, L. Index Interactions in Physical Design Tuning: Modeling, Analysis, and Applications. International Conference on Very Large Data Bases (2009).PDF icon schnaitter-vldb09.pdf (743.29 KB)
Licamele, L. & Getoor, L. Indirect two-sided relative ranking: a robust similarity measure for gene expression data. BMC Bioinformatics (2010).
Namata, G. Mark, Getoor, L. & Diehl, C. Inferring Organizational Titles in Online Communications. ICML Workshop on Statistical Network Analysis (2006).PDF icon icml2006_ExtAbst.pdf (72.39 KB)
Bilgic, M. Information Acquisition in Structured Domains. (2010).PDF icon mbilgic-phdthesis.pdf (4.68 MB)
Kang, H., Getoor, L., Shneiderman, B., Bilgic, M. & Licamele, L. Interactive Entity Resolution in Relational Data: A Visual Analytic Tool and Its Evaluation. IEEE Transactions on Visualization and Computer Graphics 14, 999–1014 (2008).PDF icon kang-tvcg08.pdf (3.63 MB)
Ramesh, A., Goldwasser, D., Huang, B., Daume, III, H. & Getoor, L. Interpretable Engagement Models for MOOCs using Hinge-loss Markov Random Fields. TLT 14, 1-1 (2019).PDF icon ramesh-tlt19.pdf (4.3 MB)
Getoor, L. An Introduction to Probabilistic Graphical Models for Relational Data. Data Engineering Bulletin 29, (2006).
Getoor, L. & Taskar, B. Introduction to Statistical Relational Learning. (The MIT Press, 2007).
Bhattacharya, I. & Getoor, L. Iterative Record Linkage for Cleaning and Integration. ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery (DMKD) (2004).PDF icon bhattacharyasigmod04-wkshp.pdf (222.38 KB)
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Pujara, J., Miao, H. & Getoor, L. Joint Judgments with a Budget: Strategies for Reducing the Cost of Inference. ICML Workshop on Machine Learning with Test-Time Budgets (2013).PDF icon pujara_wtbudg13.pdf (221.26 KB)
Sridhar, D., Foulds, J., Walker, M., Huang, B. & Getoor, L. Joint Models of Disagreement and Stance in Online Debate. Annual Meeting of the Association for Computational Linguistics (ACL) (2015).PDF icon sridhar-acl15.pdf (227.14 KB)

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