Publications

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P
London, B., Huang, B., Taskar, B. & Getoor, L. PAC-Bayesian Collective Stability. Proceedings of the 17th International Conference on Artificial Intelligence and Statistics (2014).PDF icon london-aistats14.pdf (490.14 KB)
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)
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).
Bach, S. H., Huang, B., Boyd-Graber, J. & Getoor, L. Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs. International Conference on Machine Learning (ICML) (2015).PDF icon bach-icml15.pdf (356.46 KB)
Elsayed, T., Oard, D., Namata, G. Mark & Getoor, L. Personal Name Resolution in Email: A Heuristic Approach. (2008).PDF icon LAMP_150.pdf (397.61 KB)
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)
Namata, G. Mark & Getoor, L. A Pipeline Approach to Graph Identification. Seventh International Workshop on Mining and Learning with Graphs (2009).PDF icon namatag-mlg09.pdf (93.77 KB)
Sen, P., Deshpande, A. & Getoor, L. PrDB: Managing and Exploiting Rich Correlations in Probabilistic Databases. VLDB Journal, special issue on uncertain and probabilistic databases (2009).PDF icon sen-vldbj09.pdf (1.12 MB)
Lansky, A. & Getoor, L. Practical Planning in COLLAGE. Proceedings of the AAAI Fall Symposium on Planning and Learning: On to Real Applications (1994).
Rastegari, M., Choi, J., Fakhraei, S., III, H. Daume & Davis, L. Predictable Dual-View Hashing. Proceedings of the 30th International Conference on Machine Learning (ICML-13) 1328–1336 (JMLR, 2013).PDF icon rastegari13.pdf (2.35 MB)
Tomkins, S., Ramesh, A. & Getoor, L. Predicting Post-Test Performance from Online Student Behavior: A High School MOOC Case Study. International Conference on Educational Data Mining (EDM) (2016).PDF icon tomkins-edm16.pdf (619.77 KB)
Licamele, L. & Getoor, L. Predicting Protein-Protein Interactions Using Relational Features. ICML Workshop on Statistical Network Analysis (2006).
Zheleva, E. Prediction, Evolution and Privacy in Social and Affiliation Networks. (2011).PDF icon zheleva-phdthesis11.pdf (5.81 MB)
Zheleva, E. & Getoor, L. Preserving the Privacy of Sensitive Relationships in Graph Data. Proceedings of the First SIGKDD International Workshop on Privacy, Security, and Trust in KDD (PinKDD 2007) 4890, 153-171 (Springer, 2008).
Zheleva, E. & Getoor, L. Preserving the Privacy of Sensitive Relationships in Graph Data. First ACM SIGKDD Workshop on Privacy, Security, and Trust in KDD (PinKDD 2007) (2007).PDF icon zheleva-pinkdd07.pdf (373.86 KB)
Zheleva, E., Terzi, E. & Getoor, L. Privacy in Social Networks. (Morgan & Claypool Publishers, 2012).
Zheleva, E. & Getoor, L. Social Network Data Analytics (Aggarwal, C.) 247–276 (Springer, 2011).
Sridhar, D., Fakhraei, S. & Getoor, L. A Probabilistic Approach for Collective Similarity-based Drug-Drug Interaction Prediction. Bioinformatics (2016).PDF icon sridhar-bioinformatics_2016.pdf (1.94 MB)
Plangprasopchok, A., Lerman, K. & Getoor, L. A Probabilistic Approach for Learning Folksonomies from Structured Data. Fourth ACM International Conference on Web Search and Data Mining (WSDM) (2011).
Ramesh, A. A Probabilistic Approach to Modeling Socio-Behavioral Interactions. (2016).PDF icon ramesh-thesis16.pdf (865.41 KB)
Sridhar, D. & Getoor, L. Probabilistic Inference for Causal Structure Discovery. Uncertainty in Artificial Intelligence (UAI) Workshop on Causation (2016).PDF icon sridhar-uai-open-problem-v2.pdf (118.31 KB)
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).
Pujara, J. Probabilistic Models for Scalable Knowledge Graph Construction. (2016).PDF icon pujara-thesis15.pdf (1.06 MB)
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., Friedman, N., Koller, D., Pfeffer, A. & Taskar, B. An Introduction to Statistical Relational Learning (Getoor, L. & Taskar, B.) (MIT Press, 2007).PDF icon srlbook-ch5.pdf (648.15 KB)
Broecheler, M., Mihalkova, L. & Getoor, L. Probabilistic Similarity Logic. Conference on Uncertainty in Artificial Intelligence (2010).PDF icon broecheler-uai10.pdf (399.54 KB)
Broecheler, M. & Getoor, L. Probabilistic Similarity Logic. International Workshop on Statistical Relational Learning (SRL'09) (2009).PDF icon broecheler-srl09.pdf (176.13 KB)
Bach, S. H., Huang, B. & Getoor, L. Probabilistic Soft Logic for Social Good. KDD Workshop on Data Science for Social Good (2014).PDF icon bach-dssg14.pdf (124.88 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)
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)
Getoor, L. & Scheffer, T. Proceedings of the 28th International Conference on Machine Learning. Proceedings of the 28th International Conference on Machine Learning (2011).
Singh, L., Getoor, L. & Licamele, L. Pruning Social Networks Using Structural Properties and Descriptive Attributes. IEEE International Conference on Data Mining (ICDM) 773-776 (2005).PDF icon singh_icdm05.pdf (149.45 KB)
Q
Rekatsinas, T. Quality-Aware Data Source Management. (2015).
Bhattacharya, I., Licamele, L. & Getoor, L. Query-Time Entity Resolution. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2006).PDF icon kdd06.pdf (183.45 KB)
Namata, G. Mark, London, B., Getoor, L. & Huang, B. Query-driven Active Surveying for Collective Classification. Workshop on Mining and Learning with Graphs (2012).PDF icon namata-mlg12.pdf (257.49 KB)
Bhattacharya, I. & Getoor, L. Query-time Entity Resolution. Journal of Artificial Intelligence Research (JAIR) 30, 621–657 (2007).PDF icon bhattacharya07a.pdf (309.63 KB)
R
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)
Sen, P., Deshpande, A. & Getoor, L. Read-Once Functions and Query Evaluation in Probabilistic Databases. International Conference on Very Large Data Bases (2010).PDF icon draft.pdf (322 KB)
Pujara, J., London, B. & Getoor, L. Reducing Label Cost by Combining Feature Labels and Crowdsourcing. ICML Workshop on Combining Learning Strategies to Reduce Label Cost (2011).PDF icon clsicml_pujara_london.pdf (253.29 KB)
Bilgic, M. & Getoor, L. Reflect and Correct: A Misclassification Prediction Approach to Active Inference. ACM Transactions on Knowledge Discovery from Data 3, 1–32 (2009).PDF icon bilgic-tkdd09.pdf (3.66 MB)
Bhattacharya, I., Licamele, L. & Getoor, L. Relational Clustering for Entity Resolution Queries. ICML Workshop on Statistical Relational Learning (SRL) (2006).PDF icon bhattacharyaicml06-wkshp.pdf (195.79 KB)
Bhattacharya, I. & Getoor, L. Relational Clustering for Multi-type Entity Resolution. ACM SIGKDD Workshop on Multi Relational Data Mining (MRDM) (2005).PDF icon bhattacharyakdd05-whskp.pdf (259.82 KB)
Diehl, C., Namata, G. Mark & Getoor, L. Relationship Identification for Social Network Discovery. AAAI '07: Proceedings of the 22nd National Conference on Artificial Intelligence (2007).PDF icon diehl-aaai07.pdf (139.6 KB)
Sen, P., Deshpande, A. & Getoor, L. Representing Tuple and Attribute Uncertainty in Probabilistic Databases. Workshop on Data Mining of Uncertain Data (ICDM) (2007).PDF icon dune07.pdf (176.67 KB)
Sen, P. & Deshpande, A. Representing and Querying Correlated Tuples in Probabilistic Databases. International Conference on Data Engineering (2007).PDF icon icde07_final.pdf (309.63 KB)
Sen, P. Representing and Querying Uncertain Data. (2009).PDF icon thesis.pdf (1.12 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)
Elsayed, T., Oard, D. & Namata, G. Mark. Resolving Personal Names in Email Using Context Expansion. 46th Annual Meeting of the Association of Computational Linguistics 265–268 (2008).PDF icon elsayed-acl08.pdf (294.84 KB)
Bach, S. H., Huang, B. & Getoor, L. Rounding Guarantees for Message-Passing MAP Inference with Logical Dependencies. NIPS Workshop on Discrete and Combinatorial Problems in Machine Learning (DISCML) (2014).PDF icon bach-discml14.pdf (254.9 KB)

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