Theses

Probabilistic Models for Scalable Knowledge Graph Construction. Jay Pujara. (2016) Ph.D. thesis, University of Maryland, College Park.
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Fundamental Properties of Feature Selection in fMRI Data. Jay Pujara. (2005) Master's thesis, Carnegie Mellon University.
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Journals and Magazines

Artificial intelligence for modeling complex systems: taming the complexity of expert models to improve decision making. Yolanda Gil, Daniel Garijo, Deborah Khider, Craig Knoblock, Varun Ratnakar, Maximiliano Osorio, Hernan Vargas, Minh Pham, Jay Pujara, and Basel Shbita. (2021) ACM Transactions on Interactive Intelligent Systems 11(2).
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Generating and Understanding Personalized Explanations in Hybrid Recommender Systems. Pigi Kouki, James Schaffer, Jay Pujara, John O'Donovan, and Lise Getoor. (2020) ACM Transactions on Interactive Intelligent Systems 10(4).
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Learning Cell Embeddings for Understanding Table Layouts. Majid Ghasemi-Gol, Jay Pujara, and Pedro Szekely. (2020) Knowledge and Information Systems 1(64).
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Collective Entity Resolution in Multi-relational Familial Networks. Pigi Kouki, Jay Pujara, Christopher Marcum, Laura Koehly, and Lise Getoor. (2018) Knowledge and Information Systems 61(3).
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Using Semantics & Statistics to Turn Data into Knowledge. Jay Pujara, Hui Miao, Lise Getoor, and William W. Cohen. (2015) AI Magazine 36(1).
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Refereed Conferences

Lawyers are Dishonest? Quantifying Representational Harms in Commonsense Knowledge Resources. Nina Mehrabi, Pei Zhou, Fred Morstatter, Jay Pujara, Xiang Ren, and Aram Galstyan. (2021) Conference on Empirical Methods in Natural Language Processing.
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RICA: Evaluating Robust Inference Capabilities Based on Commonsense Axioms. Pei Zhou, Rahul Khanna, Seyeon Lee, Bill Yuchen Lin, Daniel Ho, Jay Pujara, and Xiang Ren. (2021) Conference on Empirical Methods in Natural Language Processing.
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Probing Commonsense Explanation in Dialogue Response Generation. Pei Zhou, Pegah Jandaghi, Hyundong Cho, Bill Yuchen Lin, Jay Pujara, and Xiang Ren. (2021) Findings of the Association for Computational Linguistics: EMNLP 2021.
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Numeracy enhances the Literacy of Language Models. Avijit Thawani, Jay Pujara, and Filip Ilievski. (2021) Conference on Empirical Methods in Natural Language Processing.
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Table-based Fact Verification With Salience-aware Learning. Fei Wang, Kexuan Sun, Jay Pujara, Pedro Szekely, and Muhao Chen. (2021) Findings of the Association for Computational Linguistics: EMNLP 2021.
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Commonsense-Focused Dialogues for Response Generation An Empirical Study. Pei Zhou, Karthik Gopalakrishnan, Behnam Hedayatnia, Seokhwan Kim, Jay Pujara, Xiang Ren, Yang Liu, and Dilek Hakkani-Tur. (2021) Proceedings of the Special Interest Group on Discourse and Dialogue.
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A Graph-based Approach for Inferring Semantic Descriptions of Wikipedia Tables. Binh Vu, Craig Knoblock, Pedro Szekely, Jay Pujara, and Minh Pham. (2021) International Semantic Web Conference.
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Tabular Functional Block Detection with Embedding-based Agglomerative Cell Clustering. Kexuan Sun, Fei Wang, Muhao Chen, and Jay Pujara. (2021) Conference on Information and Knowledge Management.
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Representing Numbers in NLP: a Survey and a Vision. Avijit Thawani, Jay Pujara, Pedro Szekely, and Filip Ilievski. (2021) Conference of the North American Chapter of the Association for Computational Linguistics (NAACL).
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SPADE: A Semi-supervised Probabilistic Approach for Detecting Errors in Tables. Minh Pham, Craig Knoblock, Muhao Chen, Binh Vu, and Jay Pujara. (2021) International Joint Conference on Aritificial Intelligence (IJCAI).
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A Hybrid Probabilistic Approach for Table Understanding. Kexuan Sun, Harsha Rayudu, and Jay Pujara. (2021) Conference on Artificial Intelligence (AAAI).
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A Common Framework for Developing Table Understanding Models. Jay Pujara, Arunkumar Rajendran, Majid Ghasemi-Gol, and Pedro Szekely. (2019) International Semantic Web Conference - Posters.
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Personalized Explanations for Hybrid Recommender Systems. Pigi Kouki, James Schaffer, Jay Pujara, John O'Donovan, and Lise Getoor. (2019) ACM International Conference on Intelligent User Interfaces.
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Learning Data Transformations with Minimal User Effort. Minh Pham, Craig Knoblock, and Jay Pujara. (2019) IEEE BigData Conference.
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D-REPR: A Language for Describing and Mapping Diversely-Structured Data Sources to RDF. Binh Vu, Craig Knoblock, and Jay Pujara. (2019) ACM International Conference on Knowledge Capture (K-CAP).
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T2WML: Table To Wikidata Mapping Langauge. Pedro Szekely, Daniel Garijo, Divij Bhatia, Jiasheng Wu, Yixiang Yao, and Jay Pujara. (2019) ACM International Conference on Knowledge Capture (K-CAP).
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Tabular Cell Classification Using Pre-Trained Cell Embeddings. Majid Ghasemi-Gol, Jay Pujara, and Pedro Szekely. (2019) International Conference on Data Mining.
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Learning Semantic Models of Data Sources Using Probabilistic Graphical Models. Binh Vu, Craig Knoblock, and Jay Pujara. (2019) The Web Conference.
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Scalable Probabilistic Causal Structure Discovery. Dhanya Sridhar, Jay Pujara, and Lise Getoor. (2018) International Joint Conference on Artificial Intelligence.
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Collective Entity Resolution in Familial Networks. Pigi Kouki, Jay Pujara, Christopher Marcum, Laura Koehly, and Lise Getoor. (2017) IEEE International Conference on Data Mining.
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Sparsity and Noise: Where Knowledge Graph Embeddings Fall Short. Jay Pujara, Eriq Augustine, and Lise Getoor. (2017) Conference on Empirical Methods in Natural Language Processing (EMNLP).
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User Preferences for Hybrid Explanations. Pigi Kouki, James Schaffer, Jay Pujara, John O'Donovan, and Lise Getoor. (2017) ACM Conference on Recommender Systems.
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Disambiguating Energy Disaggregation: A Collective Probabilistic Approach. Sabina Tomkins, Jay Pujara, and Lise Getoor. (2017) International Joint Conference on Artificial Intelligence.
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Probabilistic Visitor Stitching on Cross-Device Web Logs. Sungchul Kim, Nikhil Kini, Jay Pujara, Eunyee Koh, and Lise Getoor. (2017) World Wide Web Conference.
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Unsupervised Models for Predicting Strategic Relations between Organizations. Shachi Kumar, Jay Pujara, Lise Getoor, David Mares, Dipak Gupta, and Ellen Riloff. (2016) International Conference on Advances in Social Networks Analysis and Mining.
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Budgeted Online Collective Inference. Jay Pujara, Ben London, and Lise Getoor. (2015) Uncertainty and Artificial Intelligence (UAI).
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RELLY: Inferring Hypernym Relationships Between Relational Phrases. Adam Grycner, Gerhard Weikum, Jay Pujara, James Foulds, and Lise Getoor. (2015) Conference on Empirical Methods in Natural Language Processing.
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Knowledge Graph Identification. Jay Pujara, Hui Miao, Lise Getoor, and William W. Cohen. (2013) International Semantic Web Conference (ISWC).
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Using Classifier Cascades for Scalable E-Mail Classification. Jay Pujara, Hal Daumé III, and Lise Getoor. (2011) Collaboration, Electronic Messaging, Anti-Abuse and Spam Conference.
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Refereed Workshops and Symposia

Finding Pragmatic Differences Between Disciplines. Lee Kezar and Jay Pujara. (2021) NAACL Workshop on Scholarly Document Processing.
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Story Generation with Commonsense Knowledge Graphs and Axioms. Filip Ilievski, Jay Pujara, and Hanzhi Zhang. (2021) AKBC Workshop on Commonsense Reasoning and Knowledge Bases.
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Human-like Time Series Summaries via Trend Utility Estimation. Pegah Jandaghi and Jay Pujara. (2020) Ninth International Workshop on Statistical Relational AI.
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Collective Alignment of Large-scale Ontologies. Varun Embar, Jay Pujara, and Lise Getoor. (2019) AKBC Workshop on Federated KBs and the Open Knowledge Network.
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Enterprise OKN: A Federated Knowledge Graph for Financial Data. Jay Pujara, Louiqa Raschid, Gerard Hoberg, Gordon Phillips, and Craig Knoblock. (2019) AKBC Workshop on Federated KBs and the Open Knowledge Network.
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An Intelligent Interface for Integrating Climate, Hydrology, Agriculture, and Socioeconomic Models. Daniel Garijo, Deborah Khider, Varun Ratnakar, Yolanda Gil, Ewa Deelman, Rafael Ferreira Silva, Craig Knoblock, Yao-Yi Chiang, Minh Pham, Jay Pujara, Binh Vu, Dan Feldman, Rajiv Mayani, Kelly Cobourn, Chris Duffy, Armen Kemanian, Lele Shu, Vipin Kumar, Ankush Khandelwal, Kshitij Tayal, Scott Peckham, Maria Stoica, Anna Dabrowski, Daniel Hardesty-Lewis, and Suzanne Pierce. (2019) Proceedings of the 24th International Conference on Intelligent User Interfaces: Companion.

Extensible and Scalable Entity Resolution for Financial Datasets Using RLTK. Yixiang Yao, Pedro Szekely, and Jay Pujara. (2019) SIGMOD Workshop on Data Science for Macro-modeling with Financial and Economic Datasets.
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Parsing, Representing, and Transforming Units of Measure. Basel Shbita, Arunkumar Rajendran, Jay Pujara, and Craig Knoblock. (2019) Modeling the World's Systems.
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Aligning Product Categories using Anchor Products. Varun Embar, Golnoosh Farnadi, Jay Pujara, and Lise Getoor. (2018) WSDM Workshop on Knowledge Base Construction, Reasoning and Mining.
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Hybrid Link Prediction for Competitor Relationships. Jay Pujara. (2018) Fourth International Workshop on Data Science for Macro-Modeling with Financial and Economic Datasets.
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Feature Selection Methods For Understanding Business Competitor Relationships. Rahul Gupta, Jay Pujara, Craig A. Knoblock, Shushyam M. Sharanappa, Bharat Pulavarti, Gerard Hoberg, and Gordon Phillips. (2018) Fourth International Workshop on Data Science for Macro-Modeling with Financial and Economic Datasets.
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Using Noisy Extractions to Discover Causal Knowledge. Dhanya Sridhar, Jay Pujara, and Lise Getoor. (2018) Sixth Workshop on Automated Knowledge Base Construction.
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Extracting Knowledge Graphs from Financial Filings. Jay Pujara. (2017) Third International Workshop on Data Science for Macro-Modeling with Financial and Economic Datasets.
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Generic Statistical Relational Entity Resolution in Knowledge Graphs. Jay Pujara and Lise Getoor. (2016) Sixth International Workshop on Statistical Relational AI.
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Adaptive Neighborhood Graph Construction for Inference in Multi-Relational Networks. Shobeir Fakhraei, Dhanya Sridhar, Jay Pujara, and Lise Getoor. (2016) 12th International Workshop on Mining and Learning with Graphs (MLG).
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Online Inference for Knowledge Graph Construction.. Jay Pujara, Ben London, Lise Getoor, and William W. Cohen. (2015) Fifth International Workshop on Statistical Relational AI.
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Probabilistic Models for Collective Entity Resolution Between Knowledge Graphs. Jay Pujara, Kevin Murphy, Xin Luna Dong, and Curtis Janssen. (2014) Bay Area Machine Learning Symposium.
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Building Dynamic Knowledge Graphs. Jay Pujara and Lise Getoor. (2014) Fourth Workshop on Automated Knowledge Base Construction.
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A Unified Probabilistic Approach for Semantic Clustering of Relational Phrases. Adam Grycner, Gerhard Weikum, Jay Pujara, James Foulds, and Lise Getoor. (2014) Fourth Workshop on Automated Knowledge Base Construction.
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Large-Scale Knowledge Graph Identification using PSL. Jay Pujara, Hui Miao, Lise Getoor, and William W. Cohen. (2013) Workshop on Structured Learning.
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Joint Judgments with a Budget: Strategies for Reducing the Cost of Inference. Jay Pujara, Hui Miao, and Lise Getoor. (2013) Workshop on Machine Learning with Test-Time Budgets.
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Ontology-Aware Partitioning for Knowledge Graph Identification. Jay Pujara, Hui Miao, Lise Getoor, and William W. Cohen. (2013) Third Workshop on Automatic Knowledge Base Construction.
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Extended Abstract: Large-Scale Knowledge Graph Identification using PSL. Jay Pujara, Hui Miao, Lise Getoor, and William W. Cohen. (2013) AAAI Fall Symposium on Semantics for Big Data.
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Large-Scale Hierarchical Topic Models. Jay Pujara and Peter Skomoroch. (2012) Workshop on Big Learning.
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Social Group Modeling with Probabilistic Soft Logic. Bert Huang, Stephen H. Bach, Eric Norris, Jay Pujara, and Lise Getoor. (2012) Workshop on Social Network and Social Media Analysis: Methods, Models, and Applications.
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Facilitating Medication Reconciliation with Animation and Spatial Layout. Leo Claudino, Sameh Khamis, Ran Liu, Ben London, Jay Pujara, Catherine Plaisant, and Ben Shneiderman. (2011) Workshop on Interactive Healthcare Systems.
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Reducing Label Cost by Combining Feature Labels and Crowdsourcing. Jay Pujara, Ben London, and Lise Getoor. (2011) Workshop on Combining Learning Strategies to Reduce Label Cost.
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Coarse-to-Fine, Cost-Sensitive Classification of E-Mail. Jay Pujara and Lise Getoor. (2010) Workshop on Coarse-to-Fine Processing.
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Patents

User Trustworthiness. Jay Pujara, Vishwanath Ramarao, Xiaopeng Xi, Martin Zinkevich, Anirban Dasgupta, Belle Tseng, Wei Chu, and Gareth Shue. (2016) Patent 9519682.

Real-Time Ad-Hoc Spam Filtering of E-Mail. Jay Pujara. (2011) Patent 8069128.

Employing Pixel Density to Detect a Spam Image. Ke Wei, Hao Zheng, and Jay Pujara. (2011) Patent 7882177.

Identifying IP Addresses for Spammers. Jaesik Choi, Jay Pujara, Vishwanath Ramarao, and Ke Wei. (2010) Patent 7849146.