Publications

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Getoor, L., Friedman, N., Koller, D. & Taskar, B. Learning Probabilistic Models of Relational Structure. Proceedings of International Conference on Machine Learning (ICML) (2001).PDF icon icml01.pdf (157.91 KB)
Getoor, L., Friedman, N., Koller, D. & Pfeffer, A. Relational Data Mining (Dzeroski, S. & Lavrac, N.) (Springer-Verlag, 2001).
Getoor, L. Learning Statistical Models from Relational Data. (2001).PDF icon getoor-thesis.pdf (3.39 MB)
Getoor, L. Multi-relational Data Mining Using Probabilistic Models. Multi-Relational Data Mining Workshop (2001).PDF icon mrdm.pdf (109.57 KB)
Getoor, L., Segal, E., Taskar, B. & Koller, D. Probabilistic Models of Text and Link Structure for Hypertext Classification. IJCAI Workshop on Text Learning: Beyond Supervision (2001).PDF icon ijcai01-ws.pdf (127.03 KB)
Getoor, L., Koller, D. & Taskar, B. Selectivity estimation using probabilistic relational models. Proceedings of ACM-SIGMOD 2001 International Conference on Management of Data (2001).PDF icon sigmod01.pdf (471.72 KB)
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., Taskar, B. & Friedman, N. Learning Probabilistic Relational Models with Structural Uncertainty. Proceedings of the AAAI Workshop on Learning Statistical Models from Relational Data (2000).
Getoor, L. & Sahami, M. Using Probabilistic Relational Models for Collaborative Filtering. Working Notes of the KDD Workshop on Web Usage Analysis and User Profiling (1999).
Getoor, L., Ottosson, G., Fromherz, M. & Carlson, B. Effictive Redundant Constraints for Online Scheduling. Proceedings of the Fourteenth national Conference on Artificial Intelligence (1997).
Getoor, L. & Fromherz, M. Online Scheduling for Reprographic Machines. Working notes AAAI Workshop on Online Search (1997).
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., Friedman, N., Koller, D. & Pfeffer, A. Learning Probabilistic Relational Models. Relational Data Mining (Springer-Verlag, 2001).PDF icon lprm-ch.pdf (376 KB)
Grycner, A., Weikum, G., Pujara, J., Foulds, J. & Getoor, L. RELLY: Inferring Hypernym Relationships Between Relational Phrases. Conference on Empirical Methods in Natural Language Processing (2015).PDF icon agrycner-emnlp15.pdf (234.86 KB)
Grycner, A., Weikum, G., Pujara, J., Foulds, J. & Getoor, L. A Unified Probabilistic Approach for Semantic Clustering of Relational Phrases. NIPS Workshop on Automated Knowledge Base Construction (2014).
H
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)
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)
Huang, B., Kimmig, A., Getoor, L. & Golbeck, J. A Flexible Framework for Probabilistic Models of Social Trust. The 2013 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction (SBP 2013) (2013).PDF icon huang-sbp13.pdf (247.2 KB)
Huang, B., London, B., Taskar, B. & Getoor, L. Empirical Analysis of Collective Stability. ICML Workshop on Structured Learning (SLG) (2013).PDF icon huang-slg13.pdf (237.81 KB)
Huang, B., Kimmig, A., Getoor, L. & Golbeck, J. Probabilistic Soft Logic for Trust Analysis in Social Networks. International Workshop on Statistical Relational Artificial Intelligence (StaRAI 2012) (2012).PDF icon huang-starai12.pdf (241.96 KB)
Huang, B., Bach, S. H., Norris, E., Pujara, J. & Getoor, L. Social Group Modeling with Probabilistic Soft Logic. NIPS 2012 Workshop - Social Network and Social Media Analysis: Methods, Models, and Applications (2012).
Hung, E., Getoor, L. & Subrahmanian, V. S. Probabilistic Interval XML. ACM Transactions on Computational Logic (TOCL) (2007).
Hung, E., Getoor, L. & Subrahmanian, V. S. Probabilistic Interval XML. Proceedings of the International Conference on Database Theory (2003).
Hung, E., Getoor, L. & Subrahmanian, V. S. PXML: A Probabilistic Semistructured Data Model and Algebra. Proceedings of the IEEE International Conference on Data Engineering (2003).
Hwang, H., Lauw, H., Getoor, L. & Ntoulas, A. Organizing User Search Histories. IEEE Transactions on Knowledge and Data Engineering (2010).
I
Islamaj, R., Getoor, L. & W. Wilbur, J. Computational Methods of Feature Selection (Liu, H. & Motoda, H.) (Chapman and Hall/CRC Press, 2007).
Islamaj, R., Getoor, L. & W. Wilbur, J. Characterizing RNA secondary-structure features and their effects on splice-site prediction. IEEE ICDM Workshop on Mining and Management of Biological Data (2007).
Islamaj, R., Getoor, L., W. Wilbur, J. & Mount, S. Features generated for computational splice-site prediction correspond to functional elements. BMC Bioinformatics 8, (2007).
Islamaj, R., Getoor, L., W. Wilbur, J. & Mount, S. SplicePort - An interactive splice-site analysis tool. Nucleic Acids Research (2007).PDF icon dogan-nar.pdf (1.34 MB)
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. 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)
K
Kang, J., Lerman, K. & Getoor, L. LA-LDA: A Limited Attention Topic Model for Social Recommendation. The 2013 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction (SBP 2013) (2013).PDF icon kang-sbp13.pdf (622.52 KB)
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)
Kang, H., Getoor, L. & Singh, L. C-GROUP: A Visual Analytic Tool for Pairwise Analysis of Dynamic Group Membership. Visual Analytics Science and Technology (VAST) (2007).PDF icon vast07-kang.pdf (663.26 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)
Kang, H., Getoor, L. & Singh, L. Visual Analysis of Dynamic Group Membership in Temporal Social Networks. SIGKDD Explorations, Special Issue on Visual Analytics 9, 13-21 (2007).PDF icon 2_kang-CGROUP_1207.pdf (1.48 MB)
Kim, S., Kini, N., Pujara, J., Koh, E. & Getoor, L. Probabilistic Visitor Stitching on Cross-Device Web Logs. International Conference on World Wide Web (WWW) 1581–1589 (2017).PDF icon p1581-kimwww17.pdf (1.23 MB)
Kimmig, A., Mihalkova, L. & Getoor, L. Lifted graphical models: a survey. Machine Learning 1-45 (2014).
Kimmig, A., Bach, S. H., Broecheler, M., Huang, B. & Getoor, L. A Short Introduction to Probabilistic Soft Logic. NIPS Workshop on Probabilistic Programming: Foundations and Applications (2012).PDF icon psl_pp12.pdf (164.6 KB)
Kimmig, A., Memory, A., Miller, R. & Getoor, L. A Collective, Probabilistic Approach to Schema Mapping. International Conference on Data Engineering (ICDE) (2017). at <https://github.com/alexmemory/kimmig-icde17/wiki>PDF icon kimmig-icde17.pdf (463.69 KB)
Kimmig, A., Mihalkova, L. & Getoor, L. Lifted graphical models: a survey. Machine Learning Journal 99, 1–45 (2015).PDF icon kimmig-mlj15.pdf (785.58 KB)
Kimmig, A., Memory, A., Miller, R. J. & Getoor, L. A Collective, Probabilistic Approach to Schema Mapping Using Diverse Noisy Evidence. IEEE Transactions on Knowledge and Data Engineering 31, 1426-1439 (2019).PDF icon kimming-tkde19.pdf (713.64 KB)
Koller, D., Friedman, N., Getoor, L. & Taskar, B. An Introduction to Statistical Relational Learning (Getoor, L. & Taskar, B.) (MIT Press, 2007).PDF icon srlbook-ch2.pdf (513.11 KB)
Kouki, P., Pujara, J., Marcum, C., Koehly, L. & Getoor, L. Collective Entity Resolution in Familial Networks. IEEE International Conference on Data Mining (ICDM) (2017). at <https://github.com/pkouki/icdm2017>PDF icon kouki-icdm17.pdf (653.4 KB)
Kouki, P., Schaffer, J., Pujara, J., ODonovan, J. & Getoor, L. User Preferences for Hybrid Explanations. 11th ACM Conference on Recommender Systems (RecSys) (2017).PDF icon kouki-recsys17.pdf (2.64 MB)
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)
Kouki, P., Marcum, C., Koehly, L. & Getoor, L. Entity Resolution in Familial Networks. 12th International Workshop on Mining and Learning with Graphs (2016).PDF icon kouki-mlg16.pdf (633.08 KB)
Kouki, P., Pujra, J., Marcum, C., Koehly, L. & Getoor, L. Collective Entity Resolution in Multi-Relational Familial Networks. Knowledge and Information Systems (KAIS) (2018).PDF icon kouki-kais18.pdf (1.17 MB)
Kouki, P. Resolution, Recommendation, and Explanation in Richly Structured Social Networks. Technology and Information Management Ph.D. Thesis, (2018).PDF icon kouki-dissertation.pdf (6.94 MB)
Kouki, P., Schaffer, J., Pujara, J., ODonovan, J. & Getoor, L. Personalized Explanations for Hybrid Recommender Systems. Intelligent User Interfaces (2019).PDF icon kouki-iui19.pdf (3.34 MB)

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