Publications

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G
L. Getoor, Friedman, N., Koller, D., and Taskar, B., Learning Probabilistic Models of Link Structure, Journal of Machine Learning Research, vol. 3, p. 679- -707, 2002.PDF icon jmlr02.pdf (502.22 KB)
L. Getoor, Friedman, N., and Koller, D., Learning Structured Statistical Models from Relational Data, Electronic Transactions on Artificial Intelligence, vol. 6, 2002.
L. Getoor, Friedman, N., Koller, D., and Taskar, B., Learning Probabilistic Models of Relational Structure, in Proceedings of International Conference on Machine Learning (ICML), 2001.PDF icon icml01.pdf (157.91 KB)
L. Getoor, Friedman, N., Koller, D., and Pfeffer, A., Learning Probabilistic Relational Models, 1st ed., vol. 1. Springer-Verlag, 2001, p. 307--335.
L. Getoor, Learning Statistical Models from Relational Data, Stanford, 2001.PDF icon getoor-thesis.pdf (3.39 MB)
L. Getoor, Multi-relational Data Mining Using Probabilistic Models, in Multi-Relational Data Mining Workshop, 2001.PDF icon mrdm.pdf (109.57 KB)
L. Getoor, Segal, E., Taskar, B., and Koller, D., Probabilistic Models of Text and Link Structure for Hypertext Classification, in IJCAI Workshop on Text Learning: Beyond Supervision, 2001.PDF icon ijcai01-ws.pdf (127.03 KB)
L. Getoor, Koller, D., and Taskar, B., Selectivity estimation using probabilistic relational models, in Proceedings of ACM-SIGMOD 2001 International Conference on Management of Data, 2001.PDF icon sigmod01.pdf (471.72 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., Taskar, B., and Friedman, N., Learning Probabilistic Relational Models with Structural Uncertainty, in Proceedings of the AAAI Workshop on Learning Statistical Models from Relational Data, 2000.
L. Getoor and Sahami, M., Using Probabilistic Relational Models for Collaborative Filtering, in Working Notes of the KDD Workshop on Web Usage Analysis and User Profiling, 1999.
L. Getoor, Ottosson, G., Fromherz, M., and Carlson, B., Effictive Redundant Constraints for Online Scheduling, in Proceedings of the Fourteenth national Conference on Artificial Intelligence, 1997.
L. Getoor and Fromherz, M., Online Scheduling for Reprographic Machines, in Working notes AAAI Workshop on Online Search, 1997.
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, Friedman, N., Koller, D., and Pfeffer, A., Learning Probabilistic Relational Models, in Relational Data Mining, 2001.PDF icon lprm-ch.pdf (376 KB)
A. Grycner, Weikum, G., Pujara, J., Foulds, J., and Getoor, L., RELLY: Inferring Hypernym Relationships Between Relational Phrases, in Conference on Empirical Methods in Natural Language Processing, 2015.PDF icon agrycner-emnlp15.pdf (234.86 KB)
A. Grycner, Weikum, G., Pujara, J., Foulds, J., and Getoor, L., A Unified Probabilistic Approach for Semantic Clustering of Relational Phrases, in NeurIPS, 2014.
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H. Haidarian-Shahri, Namata, G. Mark, Navlakha, S., Deshpande, A., and Roussopoulos, N., A Graph-based Approach to Vehicle Tracking in Traffic Camera Video Streams, in 4th International Workshop on Data Management for Sensor Networks, 2007.PDF icon dmsn07.pdf (576.07 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)
S. Hossam, Lisa, S., Getoor, L., and Janet, M., Stability vs. Diversity: Understanding the Dynamics of Actors in Time-varying Affiliation Networks, in ICSI, 2012.PDF icon sharara-icsi12.pdf (307.98 KB)
S. Hossam, Getoor, L., and Myra, N., Active Surveying: A Probabilistic Approach for Identifying Key Opinion Leaders, in IJCAI, 2011.PDF icon sharara-ijcai11.pdf (349.39 KB)
B. Huang, Kimmig, A., Getoor, L., and Golbeck, J., A Flexible Framework for Probabilistic Models of Social Trust, in SBP, 2013.PDF icon huang-sbp13.pdf (247.2 KB)
B. Huang, London, B., Taskar, B., and Getoor, L., Empirical Analysis of Collective Stability, in ICML Workshop on SLG, 2013.PDF icon huang-slg13.pdf (237.81 KB)
B. Huang, Kimmig, A., Getoor, L., and Golbeck, J., Probabilistic Soft Logic for Trust Analysis in Social Networks, in UAI Workshop on StaRAI , 2012.PDF icon huang-starai12.pdf (241.96 KB)
E. Hung, Getoor, L., and Subrahmanian, V. S., Probabilistic Interval XML, ACM Transactions on Computational Logic (TOCL), 2007.
E. Hung, Getoor, L., and Subrahmanian, V. S., Probabilistic Interval XML, in Proceedings of the International Conference on Database Theory, 2003.
E. Hung, Getoor, L., and Subrahmanian, V. S., PXML: A Probabilistic Semistructured Data Model and Algebra, in Proceedings of the IEEE International Conference on Data Engineering, 2003.
H. Hwang, Lauw, H., Getoor, L., and Ntoulas, A., Organizing User Search Histories, IEEE Transactions on Knowledge and Data Engineering, 2010.
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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)
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)
H. Kang, Getoor, L., and Singh, L., C-GROUP: A Visual Analytic Tool for Pairwise Analysis of Dynamic Group Membership, in Visual Analytics Science and Technology (VAST), 2007.PDF icon vast07-kang.pdf (663.26 KB)
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)
H. Kang, Getoor, L., and Singh, L., Visual Analysis of Dynamic Group Membership in Temporal Social Networks, SIGKDD Explorations, Special Issue on Visual Analytics, vol. 9, pp. 13-21, 2007.PDF icon 2_kang-CGROUP_1207.pdf (1.48 MB)
S. Kim, Kini, N., Pujara, J., Koh, E., and Getoor, L., Probabilistic Visitor Stitching on Cross-Device Web Logs, in International Conference on World Wide Web (WWW), 2017, pp. 1581–1589.PDF icon p1581-kimwww17.pdf (1.23 MB)
A. Kimmig, Mihalkova, L., and Getoor, L., Lifted graphical models: a survey, Machine Learning, pp. 1-45, 2014.
A. Kimmig, Bach, S., Broecheler, M., Huang, B., and Getoor, L., A Short Introduction to Probabilistic Soft Logic, in NIPS Workshop on PPFA, 2012.PDF icon kimming-ppfa12.pdf (164.6 KB)
A. Kimmig, Memory, A., Miller, R., and Getoor, L., A Collective, Probabilistic Approach to Schema Mapping, in International Conference on Data Engineering (ICDE), 2017.PDF icon kimmig-icde17.pdf (463.69 KB)
A. Kimmig, Mihalkova, L., and Getoor, L., Lifted graphical models: a survey, Machine Learning Journal, vol. 99, pp. 1–45, 2015.PDF icon kimmig-mlj15.pdf (785.58 KB)
A. Kimmig, Memory, A., Miller, R. J., and Getoor, L., A Collective, Probabilistic Approach to Schema Mapping Using Diverse Noisy Evidence, IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 31, no. 8, p. 1426--1439, 2019.PDF icon kimming-tkde19.pdf (713.64 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)
P. Kouki, Pujara, J., Marcum, C., Koehly, L., and Getoor, L., Collective Entity Resolution in Familial Networks, in IEEE International Conference on Data Mining (ICDM), 2017.PDF icon kouki-icdm17.pdf (653.4 KB)
P. Kouki, Schaffer, J., Pujara, J., ODonovan, J., and Getoor, L., User Preferences for Hybrid Explanations, in 11th ACM Conference on Recommender Systems (RecSys), 2017.PDF icon kouki-recsys17.pdf (2.64 MB)
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)
P. Kouki, Marcum, C., Koehly, L., and Getoor, L., Entity Resolution in Familial Networks, in MLG, 2016.PDF icon kouki-mlg16.pdf (633.08 KB)

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