Publications

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London, B., Huang, B., Taskar, B. & Getoor, L. Collective Stability in Structured Prediction: Generalization from One Example. ICML (2013).PDF icon london-icml13.pdf (373.82 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)
Bhattacharya, I. & Getoor, L. Collective Relational Clustering. Constrained Clustering: Advances in Algorithms, Theory, and Applications 1, 221-244 (Chapman and Hall, 2008).PDF icon bhattacharya-book08.pdf (10.39 MB)
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)
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)
Namata, G., Kok, S. & Getoor, L. Collective Graph Identification. KDD (2011).PDF icon namata-kdd11.pdf (185.7 KB)
Namata, G., London, B. & Getoor, L. Collective Graph Identification. TKDD 10, (2015).PDF icon namata-tkdd15.pdf (500.96 KB)
Bhattacharya, I. & Getoor, L. Collective Entity Resolution in Relational Data. Data Engineering Bulletin 29, (2006).
Kouki, P., Pujara, J., Marcum, C., Koehly, L. & Getoor, L. Collective Entity Resolution in Multi-Relational Familial Networks. KAIS 61, 1547-–1581 (2018).PDF icon kouki-kais18.pdf (1.17 MB)
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)
Bhattacharya, I. & Getoor, L. Collective Entity Resolution In Relational Data. ACM Transactions on Knowledge Discovery from Data 1, 1-36 (2007).PDF icon bhattacharya-tkdd.pdf (346.13 KB)
London, B. & Getoor, L. Collective Classification of Network Data. Data Classification: Algorithms and Applications 1, 399--416 (CRC Press, 2013).PDF icon london-book13.pdf (394.37 KB)
Sen, P. et al. Collective Classification in Network Data. AI Magazine 29, 93–106 (2008).PDF icon sen-aimag08.pdf (497.82 KB)
Namata, G., Sen, P., Bilgic, M. & Getoor, L. Collective Classification for Text Classification. Text Mining: Classification, Clustering, and Applications 1, 51--69 (Taylor and Francis Group, 2009).PDF icon namata-book09.pdf (4.35 MB)
Sen, P., Namata, G. Mark, Bilgic, M. & Getoor, L. Collective Classification. Encyclopedia of Machine Learning (2010).
Embar, V., Pujara, J. & Getoor, L. Collective Alignment of Large-scale Ontologies. AKBC Workshop on FKBs (2019).
London, B. et al. Collective Activity Detection using Hinge-loss Markov Random Fields. CVPR Workshop on SPTLE (2013).PDF icon london-sptle13.pdf (705.87 KB)
Lansky, A., Friedman, M., Getoor, L., Schmidler, S. & Jr., N. Short. The Collage/Khoros Link: Planning for Image Processing Tasks. Proceedings of the AAAI Spring Symposium on Integrated Planning Applications (1995).
Zheleva, E., Sharara, H. & Getoor, L. Co-evolution of Social and Affiliation Networks. 15th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) (2009).PDF icon fp659-zheleva.pdf (900 KB)
Pujara, J. & Getoor, L. Coarse-to-Fine, Cost-Sensitive Classification of E-Mail. NIPS Workshop on Coarse-to-Fine Processing (2010).PDF icon pujara_nips10.pdf (258.86 KB)
Chang, J., Chen, R., Pujara, J. & Getoor, L. Clustering System Data using Aggregate Measures. SysML (2018).PDF icon chang-sysml18.pdf (299.32 KB)
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).
Doppa, J., Yu, J., Tadepalli, P. & Getoor, L. Chance-Constrained Programs for Link Prediction. NIPS Workshop on Analyzing Networks and Learning with Graphs (2009).PDF icon doppa-nips09wkshp.pdf (161.38 KB)
Muthiah, S. et al. Capturing Planned Protests from Open Source Indicators. AI Mag 37, 63–75 (2016).PDF icon muthiah-aimag16.pdf (1.23 MB)
Licamele, L., Bilgic, M., Getoor, L. & Roussopoulos, N. Capital and Benefit in Social Networks. ACM SIGKDD Workshop on Link Analysis and Group Detection (LinkKDD) (2005).PDF icon licamele_linkkdd05.pdf (421.14 KB)
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)
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Embar, V., Farnadi, G., Pujara, J. & Getoor, L. Aligning Product Categories using Anchor Products. KBCOM (2018).PDF icon embar-kbcom18.pdf (577.65 KB)
Fakhraei, S., Dhanya, S., Pujara, J. & Getoor, L. Adaptive Neighborhood Graph Construction for Inference in Multi-Relational Networks. KDD (ACM SIGKDD, 2016).
Sharara, H., Norton, M. & Getoor, L. Active Surveying for Leadership Identification. The International Sunbelt Social Networks Conference XXX (2010).
Hossam, S., Getoor, L. & Myra, N. Active Surveying: A Probabilistic Approach for Identifying Key Opinion Leaders. IJCAI (2011).PDF icon sharara-ijcai11.pdf (349.39 KB)
Sharara, H., Getoor, L. & Norton, M. Active Surveying. NIPS Workshop on Networks Across Disciplines in Theory and Applications (2010).
Bilgic, M., Mihalkova, L. & Getoor, L. Active Learning for Networked Data. Proceedings of the 27th International Conference on Machine Learning (ICML-10) (2010).PDF icon bilgic-icml10.pdf (515.65 KB)
Sharara, H., Getoor, L. & Norton, M. An Active Learning Approach for Identifying Key Opinion Leaders. The 2nd Workshop on Information in Networks (WIN) (2010).
Daozheng, C. et al. Active Inference for Retrieval in Camera Networks. IEEE Workshop on Person-Oriented Vision (2011).PDF icon chen-wpov11.pdf (1.53 MB)
Bilgic, M. & Getoor, L. Active Inference for Collective Classification. Twenty-Fourth Conference on Artificial Intelligence (AAAI NECTAR Track) 1652–1655 (2010).PDF icon bilgic-aaai10.pdf (387.53 KB)
Grycner, A., Weikum, G., Pujara, J., Foulds, J. & Getoor, L. A Unified Probabilistic Approach for Semantic Clustering of Relational Phrases. NeurIPS (2014).
Namata, G., Sharara, H. & Getoor, L. A Survey of Link Mining Tasks for Analyzing Noisy and Incomplete Networks. Link Mining: Models, Algorithms, and Applications 1, 107--133 (Springer, 2010).PDF icon namata-book10.pdf (656.83 KB)
Kimmig, A., Bach, S., Broecheler, M., Huang, B. & Getoor, L. A Short Introduction to Probabilistic Soft Logic. NIPS Workshop on PPFA (2012).PDF icon kimming-ppfa12.pdf (164.6 KB)
Sridhar, D., Fakhraei, S. & Getoor, L. A Probabilistic Approach for Collective Similarity-based Drug-Drug Interaction Prediction. Bioinformatics 32, (2016).PDF icon sridhar-bioinformatics16.pdf (1.94 MB)
Huang, B., Kimmig, A., Getoor, L. & Golbeck, J. A Flexible Framework for Probabilistic Models of Social Trust. SBP (2013).PDF icon huang-sbp13.pdf (247.2 KB)
Islamaj, R., Getoor, L. & Wilbur, J. A Feature Generation Algorithm with Applications to Biological Sequence Classification. Computational Methods of Feature Selection 1, 355--376 (Chapman and Hall/CRC Press, 2008).PDF icon islamaj-book08.pdf (3.09 MB)
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)
Augustine, E. & Getoor, L. A Comparison of Bottom-Up Approaches to Grounding for Templated Markov Random Fields. SysML (2018). at <https://github.com/eriq-augustine/grounding-experiments>PDF icon augustine-sysml18.pdf (624.33 KB)

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