Archived Publications (Latest: https://linqs.github.io/linqs-website/publications/)

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S. H. Bach, Huang, B., and Getoor, L., “Large-margin Structured Learning for Link Ranking”, in NIPS Workshop on Frontiers of Network Analysis: Methods, Models, and Applications, 2013.PDF icon bach-fna13.pdf (210.09 KB)
J. Pujara, Miao, H., Getoor, L., and Cohen, W., “Large-Scale Knowledge Graph Identification using PSL”, in ICML Workshop on Structured Learning (SLG), 2013.PDF icon pujara_slg13.pdf (277.63 KB)
J. Pujara, Miao, H., Getoor, L., and Cohen, W., “Large-Scale Knowledge Graph Identification using PSL”, in AAAI Fall Symposium on Semantics for Big Data, 2013.PDF icon pujara_s4bd13.pdf (306.96 KB)
J. Kang, Lerman, K., and Getoor, L., “LA-LDA: A Limited Attention Topic Model for Social Recommendation”, in The 2013 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction (SBP 2013), 2013.PDF icon kang-sbp13.pdf (622.52 KB)
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J. Pujara, Miao, H., Getoor, L., and Cohen, W., “Knowledge Graph Identification”, in International Semantic Web Conference (ISWC), 2013.PDF icon pujara_iswc13.pdf (508.7 KB)
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D. Sridhar and Getoor, L., “Joint Probabilistic Inference of Causal Structure”, in KDD Workshop on CD, 2016.PDF icon sridhar-cd16.pdf (204.51 KB)
D. Sridhar, Foulds, J., Walker, M., Huang, B., and Getoor, L., “Joint Models of Disagreement and Stance in Online Debate”, in Annual Meeting of the Association for Computational Linguistics (ACL), 2015.PDF icon sridhar-acl15.pdf (227.14 KB)
J. Pujara, Miao, H., and Getoor, L., “Joint Judgments with a Budget: Strategies for Reducing the Cost of Inference”, in ICML Workshop on Machine Learning with Test-Time Budgets, 2013.PDF icon pujara_wtbudg13.pdf (221.26 KB)
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I. Bhattacharya and Getoor, L., “Iterative Record Linkage for Cleaning and Integration”, in ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery (DMKD), 2004.PDF icon bhattacharyasigmod04-wkshp.pdf (222.38 KB)
L. Getoor and Taskar, B., Introduction to Statistical Relational Learning. The MIT Press, 2007.
L. Getoor, “An Introduction to Probabilistic Graphical Models for Relational Data”, Data Engineering Bulletin, vol. 29, 2006.
A. Ramesh, Goldwasser, D., Huang, B., Daume, III, H., and Getoor, L., “Interpretable Engagement Models for MOOCs using Hinge-loss Markov Random Fields”, IEEE Transactions on Learning Technologies (TLT), vol. 14, pp. 1-1, 2019.PDF icon ramesh-tlt19.pdf (4.3 MB)
H. Kang, Getoor, L., Shneiderman, B., Bilgic, M., and Licamele, L., “Interactive Entity Resolution in Relational Data: A Visual Analytic Tool and Its Evaluation”, IEEE Transactions on Visualization and Computer Graphics, vol. 14, pp. 999–1014, 2008.PDF icon kang-tvcg08.pdf (3.63 MB)
G. Mark Namata, Getoor, L., and Diehl, C., “Inferring Organizational Titles in Online Communications”, in ICML Workshop on Statistical Network Analysis, 2006.PDF icon icml2006_ExtAbst.pdf (72.39 KB)
L. Licamele and Getoor, L., “Indirect two-sided relative ranking: a robust similarity measure for gene expression data”, BMC Bioinformatics, 2010.
K. Schnaitter, Polyzotis, N., and Getoor, L., “Index Interactions in Physical Design Tuning: Modeling, Analysis, and Applications”, in International Conference on Very Large Data Bases, 2009.PDF icon schnaitter-vldb09.pdf (743.29 KB)
L. Singh and Getoor, L., “Increasing the predictive power of affiliation networks.”, IEEE Data Engineering Bulletin, vol. 30, 2007.PDF icon singh.pdf (87.94 KB)
S. Minton, Michelson, M., See, K., Macskassy, S., Gazen, B. C., and Getoor, L., “Improving Classifier Performance by Autonomously Collecting Background Knowledge from the Web”, in Tenth International Conference on Machine Learning and Applications, 2011.PDF icon minton-icmla2011.pdf (733.09 KB)
B. London, Huang, B., and Getoor, L., “Improved Generalization Bounds for Large-scale Structured Prediction”, in NIPS Workshop on Algorithmic and Statistical Approaches for Large Social Networks, 2012.PDF icon london-nips12ws.pdf (213.95 KB)
G. Mark Namata and Getoor, L., “Identifying Graphs From Noisy and Incomplete Data”, in 1st ACM SIGKDD Workshop on Knowledge Discovery from Uncertain Data, 2009.PDF icon namatag-kddu09.pdf (241.7 KB)
S. Srinivasan, Rao, N. S., Subbaian, K., and Getoor, L., “Identifying Facet Mismatches In Search Via Micrographs”, in International Conference on Information and Knowledge Management (CIKM), 2019.PDF icon srinivasan-cikm19.pdf (887.06 KB)
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H. Miao, Liu, X., Huang, B., and Getoor, L., “A Hypergraph-Partitioned Vertex Programming Approach for Large-scale Consensus Optimization”, in 2013 IEEE International Conference on Big Data, 2013.PDF icon miao-bd13.pdf (307.51 KB)
P. Kouki, Fakhraei, S., Foulds, J., Eirinaki, M., and Getoor, L., “HyPER: A Flexible and Extensible Probabilistic Framework for Hybrid Recommender Systems”, in 9th ACM Conference on Recommender Systems (RecSys), 2015.PDF icon kouki-recsys15.pdf (1.03 MB)
S. H. Bach, Huang, B., London, B., and Getoor, L., “Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction”, in Uncertainty in Artificial Intelligence, 2013.PDF icon bach-uai13.pdf (379.45 KB)
S. H. Bach, Broecheler, M., Huang, B., and Getoor, L., “Hinge-Loss Markov Random Fields and Probabilistic Soft Logic”, Journal of Machine Learning Research (JMLR), vol. 18, pp. 1-67, 2017.PDF icon bach-jmlr17.pdf (731.56 KB)
S. H. Bach, Broecheler, M., Huang, B., and 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)
E. Zheleva, Getoor, L., and Sarawagi, S., “Higher-order Graphical Models for Classification in Social and Affiliation Networks”, in NIPS Workshop on Networks Across Disciplines: Theory and Applications, 2010.PDF icon zheleva-nips2010.pdf (200.43 KB)
X. He, Rekatsinas, T., Foulds, J., Getoor, L., and Liu, Y., “HawkesTopic: A Joint Model for Network Inference and Topic Modeling from Text-Based Cascades”, in International Conference on Machine Learning, 2015.PDF icon He2015HawkesTopic.pdf (819.91 KB)
O. Udrea, Miller, R., and Getoor, L., “HOMER: Ontology visualization and analysis”, in Demo Presentation at International Semantic Web Conference (ISWC), 2007.PDF icon homer.pdf (125.38 KB)
O. Udrea, Getoor, L., and Miller, R., “HOMER: Ontology Alignment Visualization and Analysis”. 2007.PDF icon getoor-homer07.pdf (125.38 KB)
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A. Plangprasopchok, Lerman, K., and Getoor, L., “Growing a tree in the forest: constructing folksonomies by integrating structured metadata”, in ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010.PDF icon plang-kdd10.pdf (705.71 KB)
B. Saha and Getoor, L., “Group Proximity Measure for Recommending Groups in Online Social Networks”, in 2nd ACM SIGKDD Workshop on Social Network Mining and Analysis (SNA-KDD), 2008.PDF icon kddw-saha.pdf (311.36 KB)
H. Sharara and Getoor, L., “Group Detection”, Encyclopedia of Machine Learning, 2010.
D. Koller, Friedman, N., Getoor, L., and Taskar, B., Graphical Models in a Nutshell, 1st ed., vol. 1. MIT Press, 2007, p. 13--55.PDF icon koller-book07.pdf (513.11 KB)
D. Koller, Friedman, N., Getoor, L., and Taskar, B., Graphical Models in a Nutshell, 1st ed., vol. 1. MIT Press, 2007, p. 13--55.PDF icon koller-book07.pdf (513.11 KB)
A. Deshpande, Getoor, L., and Sen, P., Graphical Models for Uncertain Data, 1st ed., vol. 1. Springer, 2009, p. 1--34.PDF icon deshpande-book09.pdf (570.7 KB)
B. London, Huang, B., and Getoor, L., “Graph-based Generalization Bounds for Learning Binary Relations”. University of Maryland College Park, 2013.PDF icon br_risk_bounds.pdf (304.54 KB)
A. Memory, Kimmig, A., Bach, S. H., Raschid, L., and Getoor, L., “Graph Summarization in Annotated Data Using Probabilistic Soft Logic”, in Proceedings of the International Workshop on Uncertainty Reasoning for the Semantic Web (URSW), 2012.PDF icon mrc_iswc12_ws.pdf (411.71 KB)
W. Moustafa, Miao, H., Deshpande, A., and Getoor, L., “GrDB: A System for Declarative and Interactive Analysis of Noisy Information Networks”, in SIGMOD, 2013.PDF icon moustafa-sigmod13.pdf (1.1 MB)
H. Kang, Sehgal, V., and Getoor, L., “GeoDDupe: A Novel Interface for Interactive Entity Resolution in Geospatial Data”, in International Conference on Information Visualization, 2007.PDF icon kangiv07.pdf (1.34 MB)
J. Pujara and Getoor, L., “Generic Statistical Relational Entity Resolution in Knowledge Graphs”, in StarAI, 2016.PDF icon pujara-starai16.pdf (151.37 KB)
P. Kouki, Schaffer, J., Pujara, J., O'Donovan, J., and Getoor, L., “Generating and Understanding Personalized Explanations in Hybrid Recommender Systems”, ACM Transactions on Interactive Intelligent Systems, 2019.PDF icon kouki-tiis19.pdf (2.01 MB)
H. Sharara, Sopan, A., Namata, G. Mark, Getoor, L., and Singh, L., “G-PARE: A Visual Analytic Tool for Comparative Analysis of Uncertain Graphs”, in IEEE Conference on Visual Analytics Science and Technology (VAST), 2011.PDF icon sharara-vast11.pdf (1.64 MB)
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H. Sayyadi and Getoor, L., “Future Rank: Ranking Scientific Articles by Predicting their Future PageRank”, in 2009 SIAM International Conference on Data Mining (SDM09), 2009.PDF icon sayyadi_futureRank_sdm09.pdf (621.55 KB)
L. Getoor, Koller, D., and Friedman, N., “From Instances to Classes in Probabilistic Relational Models”, in Proceedings of the ICML Workshop on Attribute-Value and Relational Learning: Crossing the Boundaries, 2000.
L. Getoor, Koller, D., and Friedman, N., “From Instances to Classes in Probabilistic Relational Models”, in Proceedings of the ICML Workshop on Attribute-Value and Relational Learning: Crossing the Boundaries, 2000.
T. Rekatsinas, Ghosh, S., Mekaru, S., Nsoesie, E., Brownstein, J., Getoor, L., and Ramakrishnan, N., “Forecasting Rare Disease Outbreaks Using Multiple Data Sources”, STAT ANAL DATA MIN, 2015.
T. Rekatsinas, Dong, X. Luna, Getoor, L., and Srivastava, D., “Finding Quality in Quantity: The Challenge of Discovering Valuable Sources for Integration”, in 7th Biennial Conference on Innovative Data Systems Research (CIDR `15), 2015.PDF icon rekatsinasCIDR15.pdf (396.99 KB)
H. Sharara, Singh, L., and Getoor, L., “Finding Prominent Actors in Dynamic Affiliation Networks”, Human Journal, 2012.PDF icon 105-204-1-SM.pdf (757.7 KB)
R. Islamaj, Getoor, L., W. Wilbur, J., and Mount, S., “Features generated for computational splice-site prediction correspond to functional elements”, BMC Bioinformatics, vol. 8, 2007.

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