Publications

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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)
Pujara, J., Augustine, E. & Getoor, L. Sparsity and Noise: Where Knowledge Graph Embeddings Fall Short. Conference on Empirical Methods in Natural Language Processing (EMNLP) (2017). at <https://github.com/eriq-augustine/meta-kg>PDF icon pujara-emnlp17.pdf (677.74 KB)
Rekatsinas, T., Deshpande, A., Dong, X. Luna, Getoor, L. & Srivastava, D. SourceSight: Enabling Effective Source Selection. ACM SIGMOD Conference (2016).PDF icon modde087.pdf (799.94 KB)
Rekatsinas, T. et al. SourceSeer: Forecasting Rare Disease Outbreaks Using Multiple Data Sources. 2015 SIAM International Conference on Data Mining (SDM15) (SIAM, 2015).PDF icon rekatsinasSDM2015.pdf (303.08 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)
Tomkins, S., Getoor, L., Chen, Y. & Zhang, Y. A Socio-linguistic Model for Cyberbullying Detection. International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (2018).PDF icon tomkins-asonam18.pdf (299.34 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).
Licamele, L. & Getoor, L. Social Capital in Friendship-Event Networks. IEEE International Conference on Data Mining (ICDM) (2006).
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)
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)
Lansky, A. & Getoor, L. Scope and Abstraction: Two Criteria for Localized Planning. Proceedings of the International Joint Conference on Arti cial Intelligence (1995).
Lansky, A. & Getoor, L. Scope and Abstraction: Two Criteria for Localized Planning. Proceedings of the Workshop on Theory Reformulation and Abstraction (1994).
Bach, S. H., Broecheler, M., Getoor, L. & O'Leary, D. P. Scaling MPE Inference for Constrained Continuous Markov Random Fields with Consensus Optimization. Advances in Neural Information Processing Systems (NIPS) 2663–2671 (2012).PDF icon bach-nips12.pdf (274.58 KB)
Embar, V., Sridhar, D., Farnadi, G. & Getoor, L. Scalable Structure Learning for Probabilistic Soft Logic. Workshop on Statistical Relational AI (2018).PDF icon VEmbar-StarAI2018.pdf (400.23 KB)
Sridhar, D., Pujara, J. & Getoor, L. Scalable Probabilistic Causal Structure Discovery. International Joint Conference on Artificial Intelligence (2018). at <https://bitbucket.org/linqs/causpsl/src/master/>PDF icon sridhar-ijcai18.pdf (281.32 KB)
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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)
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)
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)
Sen, P. Representing and Querying Uncertain Data. (2009).PDF icon thesis.pdf (1.12 MB)
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., 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)
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)
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)
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)
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)
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)
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)
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)
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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)
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., 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)
Rekatsinas, T. Quality-Aware Data Source Management. (2015).
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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)
Getoor, L. & Scheffer, T. Proceedings of the 28th International Conference on Machine Learning. Proceedings of the 28th International Conference on Machine Learning (2011).
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)
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)
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)
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)
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)
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)
Pujara, J. Probabilistic Models for Scalable Knowledge Graph Construction. (2016).PDF icon pujara-thesis15.pdf (1.06 MB)
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).
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)
Ramesh, A. A Probabilistic Approach to Modeling Socio-Behavioral Interactions. (2016).PDF icon ramesh-thesis16.pdf (865.41 KB)
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).
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)
Zheleva, E. & Getoor, L. Social Network Data Analytics (Aggarwal, C.) 247–276 (Springer, 2011).
Zheleva, E., Terzi, E. & Getoor, L. Privacy in Social Networks. (Morgan & Claypool Publishers, 2012).

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