Publications

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G
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. NeurIPS (2014).
Getoor, L. & Machanavajjhala, A. Entity Resolution in Big Data. KDD (2013).PDF icon getoor-kdd13.pdf (7.16 MB)
Getoor, L. & Machanavajjhala, A. Entity Resolution for Social Network Analysis and Mining. IEEE ACM International Conference on Advances in Social Networks Analysis and Mining (IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2012).
Getoor, L. & Machanavajjhala, A. Entity Resolution: Theory, Practice & Open Challenges. International Conference on Very Large Data Bases (2012).PDF icon p2018_lisegetoor_vldb2012.pdf (89.45 KB)
Getoor, L. & Machanavajjhala, A. Entity Resolution: Theory, Practice, and Open Challenges. AAAI Conference on Artificial Intelligence (2012).
Getoor, L. & Mihalkova, L. Exploiting Statistical and Relational Information on the Web and in Social Media. (2011).PDF icon getoor-sdm11.pdf (88.88 KB)
Getoor, L. & Scheffer, T. Proceedings of the 28th International Conference on Machine Learning. Proceedings of the 28th International Conference on Machine Learning (2011).
Getoor, L. & Taskar, B. Introduction to Statistical Relational Learning. (The MIT Press, 2007).
Getoor, L., Friedman, N., Koller, D., Pfeffer, A. & Taskar, B. Probabilistic Relational Models. An Introduction to Statistical Relational Learning 1, 129--174 (MIT Press, 2007).PDF icon getoor-book07.pdf (648.15 KB)
Getoor, L. An Introduction to Probabilistic Graphical Models for Relational Data. Data Engineering Bulletin 29, (2006).
Getoor, L. & Grant, J. PRL: A Logical Approach to Probabilistic Relational Models. Machine Learning Journal 62, (2006).PDF icon getoor-mlj06.pdf (685.04 KB)
Getoor, L. & Diehl, C. Link Mining: A Survey. SigKDD Explorations Special Issue on Link Mining 7, (2005).
Getoor, L. Link-based Classification. Advanced Methods for Knowledge Discovery from Complex Data 1, 189--207 (Springer-Verlag, 2005).PDF icon getoor-book05.pdf (273.43 KB)
Getoor, L., Rhee, J., Koller, D. & Small, P. Understanding Tuberculosis Epidemiology Using Probabilistic Relational Models. AI in Medicine Journal 30, 233-256 (2004).
Getoor, L. Link Mining: A New Data Mining Challenge. SIGKDD Explorations, volume 5, 85- -89 (2003).
Getoor, L. Structure Discovery Using Statistical Relational Learning. Data Engineering Bulletin 26, 11- -18 (2003).
Getoor, L., Friedman, N., Koller, D. & Taskar, B. Learning Probabilistic Models of Link Structure. Journal of Machine Learning Research 3, 679- -707 (2002).PDF icon jmlr02.pdf (502.22 KB)
Getoor, L., Friedman, N. & Koller, D. Learning Structured Statistical Models from Relational Data. Electronic Transactions on Artificial Intelligence 6, (2002).
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. Learning Probabilistic Relational Models. Relational Data Mining 1, 307--335 (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)
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Friedman, N. & Getoor, L. Efficient Learning Using Constrained Sufficient Statistics. Uncertainty99 (1999).
Friedman, N., Getoor, L., Koller, D. & Pfeffer, A. Learning Probabilistic Relational Models. International Joint Conference on Arti cial Intelligence (1999).PDF icon icjai99.pdf (156.94 KB)
Foulds, J., Kumar, S. & Getoor, L. Latent Topic Networks: A Versatile Probabilistic Programming Framework for Topic Models. International Conference on Machine Learning (ICML) (2015).PDF icon Foulds2015LatentTopicNetworks.pdf (382.53 KB)
Farnadi, G., Bach, S. H., Moens, M. - F., Getoor, L. & De Cock, M. Extending PSL with Fuzzy Quantifiers. International Workshop on Statistical Relational Artificial Intelligence (StaRAI) (2014).PDF icon farnadi-starai14.pdf (196.15 KB)
Farnadi, G., Bach, S. H., Moens, M. - F., Getoor, L. & De Cock, M. Soft quantification in statistical relational learning. Machine Learning Journal (2017).PDF icon farnadi-mlj17.pdf (1.24 MB)
Farnadi, G. et al. Statistical Relational Learning with Soft Quantifiers. International Conference on Inductive Logic Programming (ILP) (2015).PDF icon farnadi-ilp15.pdf (578.43 KB)
Farnadi, G., Babaki, B. & Getoor, L. Fairness-aware Relational Learning and Inference. AAAI Workshop on DeLBP (2018).
Farnadi, G., Babaki, B. & Getoor, L. Fairness in Relational Domains. AAAI/ACM Conference on AIES (2018).PDF icon farnadi_aies2018.pdf (418.24 KB)
Farnadi, G., Kouki, P., Thompson, S. K., Srinivasan, S. & Getoor, L. A Fairness-aware Hybrid Recommender System. RecSys Workshop on FATREC (2018).PDF icon farnadi-fatrec18.pdf (474.04 KB)
Farnadi, G., Babaki, B. & Getoor, L. A Declarative Approach to Fairness in Relational Domains. TCDE-Bulletin 42, 36--48 (2019).PDF icon farnadi-de19.pdf (365.14 KB)
Fakhraei, S., Huang, B., Raschid, L. & Getoor, L. Network-Based Drug-Target Interaction Prediction with Probabilistic Soft Logic. IEEE/ACM Transactions on Computational Biology and Bioinformatics (2014).PDF icon fakhraei-tcbb2014_accepted.pdf (3.97 MB)
Fakhraei, S., Huang, B. & Getoor, L. Collective Inference and Multi-Relational Learning for Drug–Target Interaction Prediction. NIPS Workshop on MLCB (2013).PDF icon fakhraei-mlcb13.pdf (243.86 KB)
Fakhraei, S., Raschid, L. & Getoor, L. Drug-Target Interaction Prediction for Drug Repurposing with Probabilistic Similarity Logic. KDD Workshop on BIOKDD (ACM, 2013).PDF icon fakhraei-biokdd13.pdf (669.27 KB)
Fakhraei, S., Foulds, J., Shashanka, M. & Getoor, L. Collective Spammer Detection in Evolving Multi-Relational Social Networks. KDD (2015).PDF icon fakhraei-kdd2015.pdf (573.89 KB)
Fakhraei, S., Onukwugha, E. & Getoor, L. Data Analytics for Pharmaceutical Discoveries. Healthcare Data Analytics 1, 1--25 (CRC Press, 2015).PDF icon fakhraei-book15.pdf (234.2 KB)
Fakhraei, S., Dhanya, S., Pujara, J. & Getoor, L. Adaptive Neighborhood Graph Construction for Inference in Multi-Relational Networks. KDD (ACM SIGKDD, 2016).

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