Eugene Agichtein's Publications

Towards Web-Scale Information Extraction

Towards Web-Scale Information Extraction [ webcast recording ] [ slides ], Eugene Agichtein, Tutorial (invited), ACM SIGKDD Webinar, 2007, Towards Web-Scale Information Extraction

Scalable Information Extraction and Integration

Scalable Information Extraction and Integration, Eugene Agichtein and Sunita Sarawagi, Tutorial at the ACM Conference on Knowledge Discovery and Data Mining (KDD 2006), 2006, Scalable Information Extraction and Integration

Web Information Extraction and User Information Needs: Towards Closing the Gap

Web Information Extraction and User Information Needs: Towards Closing the Gap, Eugene Agichtein, Position paper (invited) in the IEEE Data Engineering Bulletin issue on Web-Scale Data, Systems, and Semantics, 2006, Web Information Extraction and User Information Needs: Towards Closing the Gap

Scaling Information Extraction to Large Document Collections

Scaling Information Extraction to Large Document Collections, Eugene Agichtein, Position paper (invited) in the IEEE Data Engineering Bulletin issue on Searching and Mining Literature Digital Libraries, 2005, Scaling Information Extraction to Large Document Collections

Method for retrieving answers from an information retrieval system

Method for retrieving answers from an information retrieval system, E. Agichtein and S. Lawrence, U.S. Patent 7,269,545 (filed 2001, issued 2007), Method for retrieving answers from an information retrieval system

Training a learning system with arbitrary cost functions

Training a learning system with arbitrary cost functions, C. Burges and E. Agichtein, U.S. Patent 7,472,096 (filed 2005, issued 2008), Training a learning system with arbitrary cost functions

Modeling Information Seeker Satisfaction in Community Question Answering, Eugene Agichtein, Yandong Liu, and Jiang Bian, to appear, ACM Transactions on Knowledge Discovery from Data (TKDD), special Issue on Social Computing, Behavioral Modeling, and Prediction, 2009

Discovering Semantic Biomedical Relations utilizing the Web

Discovering Semantic Biomedical Relations utilizing the Web, Saurav Sahay, Sougata Mukherjea, Eugene Agichtein, Ernest V Garcia, Shamkant Navathe, and Ashwin Ram, ACM Transactions on Knowledge Discovery from Data, special issue on Bioinformatics, 2008, Discovering Semantic Biomedical Relations utilizing the Web

Towards a Query Optimizer for Text-Centric Tasks,

Towards a Query Optimizer for Text-Centric Tasks, Panagiotis Ipeirotis, Eugene Agichtein, Pranay Jain, and Luis Gravano, ACM Transactions on Database Systems (TODS), vol. 32, no. 4, December 2007, Towards a Query Optimizer for Text-Centric Tasks,

Learning to Find Answers to Questions on the Web

Learning to Find Answers to Questions on the Web, Eugene Agichtein, Steve Lawrence and Luis Gravano, ACM Transactions on Internet Technology (TOIT) Special Issue on "Machine Learning for the Internet", 2004, Learning to Find Answers to Questions on the Web

Extracting Synonymous Gene and Protein Terms from Biological Literature

Extracting Synonymous Gene and Protein Terms from Biological Literature, [ slides ] Hong Yu and Eugene Agichtein, Bioinformatics, also in the Intelligent Systems for Molecular Biology Conference (ISMB), 2003, Extracting Synonymous Gene and Protein Terms from Biological Literature

A note on the application of the "Boltzmann simplex"-Simulated Annealing algorithm to global optimizations of argon and water clusters

A note on the application of the "Boltzmann simplex"-Simulated Annealing algorithm to global optimizations of argon and water clusters, Francis M. Torres, Eugene Agichtein, Leonid Grinberg, Goway Yu, and Robert Q. Topper, Journal of Molecular Structure (THEOCHEM), 1997, A note on the application of the "Boltzmann simplex"-Simulated Annealing algorithm to global optimizations of argon and water clusters

Learning to Recognize Reliable Users and Content in Social Media with Coupled Mutual Reinforcement

Learning to Recognize Reliable Users and Content in Social Media with Coupled Mutual Reinforcement, Jiang Bian, Yandong Liu, Ding Zhou, Eugene Agichtein, and Hongyuan Zha, to appear in the International World Wide Web Conference (WWW), 2009, Learning to Recognize Reliable Users and Content in Social Media with Coupled Mutual Reinforcement

Classifying and Characterizing Query Intent in Sponsored Search, Azin Ashkan, Charles Clarke, Eugene Agichtein, and Qi Guo, to appear in the 31st European Conference on Informational Retrieval (ECIR), 2009

Predicting Information Seeker Satisfaction in Community Question Answering

Predicting Information Seeker Satisfaction in Community Question Answering, Yandong Liu, Jiang Bian, and Eugene Agichtein, ACM SIGIR International Conference on Research and Development in Information Retrieval (SIGIR), 2008, Predicting Information Seeker Satisfaction in Community Question Answering

Finding the Right Facts in the Crowd: Factoid Question Answering over Social Media

Finding the Right Facts in the Crowd: Factoid Question Answering over Social Media, Jiang Bian, Yandong Liu, Eugene Agichtein, and Hongyuan Zha, International World Wide Web Conference (WWW), 2008, Finding the Right Facts in the Crowd: Factoid Question Answering over Social Media

You've Got Answers: Towards Personalized Models for Predicting Success in Community Question Answering

You've Got Answers: Towards Personalized Models for Predicting Success in Community Question Answering, Yandong Liu and Eugene Agichtein, Annual Meeting of the Association of Computational Linguistics (ACL), 2008, You've Got Answers: Towards Personalized Models for Predicting Success in Community Question Answering

CoCQA: Co-Training Over Questions and Answers with an Application to Predicting Question Subjectivity Orientation

CoCQA: Co-Training Over Questions and Answers with an Application to Predicting Question Subjectivity Orientation, Baoli Li, Yandong Liu, and Eugene Agichtein, Conference on Empirical Methods in Natural Language Processing (EMNLP), 2008, CoCQA: Co-Training Over Questions and Answers with an Application to Predicting Question Subjectivity Orientation

Finding High Quality Content in Social Media

Finding High Quality Content in Social Media, Eugene Agichtein, Carlos Castillo, Debora Donato, Aristides Gionis, Gilad Mishne, ACM Web Search and Data Mining Conference (WSDM), 2008, Finding High Quality Content in Social Media

The Influence of Caption Features on Clickthrough Patterns in Web Search

The Influence of Caption Features on Clickthrough Patterns in Web Search, Charlie Clarke, Eugene Agichtein, Susan Dumais and Ryen W. White, ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2007, The Influence of Caption Features on Clickthrough Patterns in Web Search

Question Answering over Implicitly Structured Web Content

Question Answering over Implicitly Structured Web Content [ slides ], Eugene Agichtein, Chris Burges, and Eric Brill, IEEE/WIC/ACM International Conference on Web Intelligence (WI), 2007, Question Answering over Implicitly Structured Web Content

To Search or to Crawl: Towards a Query Optimizer for Text-Centric Tasks [ slides ], Panagiotis Ipeirotis, Eugene Agichtein, Pranay Jain, and Luis Gravano, ACM Conference on Management of Data (SIGMOD), 2006, Best Paper Award

Improving Web Search Ranking by Incorporating User Behavior Information [ slides ], Eugene Agichtein, Eric Brill, and Susan T. Dumais, ACM SIGIR Conference on Research and Development on Information Retrieval (SIGIR), 2006

Learning User Interaction Models for Predicting Web Search Result Preferences [ slides ], Eugene Agichtein, Eric Brill, Susan T. Dumais, and Robert Ragno, ACM SIGIR Conference on Research and Development on Information Retrieval (SIGIR), 2006

Identifying "Best Bet" Web Search Results by Mining Past User Behavior (short paper), Eugene Agichtein and Zijian Zheng, ACM Conference on Knowledge Discovery and Data Mining (SIGKDD), 2006

Confidence Estimation Methods for Partially Supervised Relation Extraction

Confidence Estimation Methods for Partially Supervised Relation Extraction (short paper), Eugene Agichtein, SIAM Conference on Data Mining (SDM), 2006, Confidence Estimation Methods for Partially Supervised Relation Extraction

Predicting Accuracy of Extracting Information from Unstructured Text Collections

Predicting Accuracy of Extracting Information from Unstructured Text Collections, [ slides ] Eugene Agichtein and Silviu Cucerzan, ACM Conference on Information and Knowledge Management (CIKM), 2005, Predicting Accuracy of Extracting Information from Unstructured Text Collections

Mining Reference Tables for Automatic Text Segmentation, [ slides ] Eugene Agichtein and Venkatesh Ganti, ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), 2004

Querying Text Databases for Efficient Information Extraction

Querying Text Databases for Efficient Information Extraction, [ slides ] Eugene Agichtein and Luis Gravano, IEEE International Conference on Data Engineering (ICDE), Best Student Paper Award, 2003, Querying Text Databases for Efficient Information Extraction

Combining Text Mining and Sequence Analysis to Discover Protein Functional Regions

Combining Text Mining and Sequence Analysis to Discover Protein Functional Regions, Eleazar Eskin and Eugene Agichtein, Pacific Symposium on Biocomputing (PSB), 2004, Combining Text Mining and Sequence Analysis to Discover Protein Functional Regions

Modeling Query-Based Access to Text Databases

Modeling Query-Based Access to Text Databases, [ slides ] Eugene Agichtein, Panagiotis Ipeirotis, and Luis Gravano, Sixth International Workshop on the Web and Databases (WebDB), 2003, Modeling Query-Based Access to Text Databases

Snowball: Extracting Relations from Large Plain-Text Collections

Snowball: Extracting Relations from Large Plain-Text Collections, [slides ] Eugene Agichtein and Luis Gravano, ACM International Conference on Digital Libraries (ACM DL), 2000, Snowball: Extracting Relations from Large Plain-Text Collections

Exploiting Diverse Knowledge Sources via Maximum Entropy in Named Entity Recognition

Exploiting Diverse Knowledge Sources via Maximum Entropy in Named Entity Recognition, Andrew Borthwick, John Sterling, Eugene Agichtein, and Ralph Grishman, Sixth Workshop on Very Large Corpora, 1998, Exploiting Diverse Knowledge Sources via Maximum Entropy in Named Entity Recognition

Understanding "Abandoned" Ads: Towards Personalized Commercial Intent Inference via Mouse Movement Analysis

Understanding "Abandoned" Ads: Towards Personalized Commercial Intent Inference via Mouse Movement Analysis, Qi Guo, Eugene Agichtein, Charles Clarke and Azin Ashkan, SIGIR 2008 Workshop on Information Retrieval in Advertising (IRA), 2008, Understanding "Abandoned" Ads: Towards Personalized Commercial Intent Inference via Mouse Movement Analysis

Characterizing Query Intent From Ad Clickthrough Data

Characterizing Query Intent From Ad Clickthrough Data, Azin Ashkan, Charles Clarke, Eugene Agichtein and Qi Guo, SIGIR 2008 Workshop on Information Retrieval in Advertising (IRA), 2008, Characterizing Query Intent From Ad Clickthrough Data

Exploring Client-Side Instrumentation for Personalized Search Intent Inference: Preliminary Experiments

Exploring Client-Side Instrumentation for Personalized Search Intent Inference: Preliminary Experiments, Qi Guo and Eugene Agichtein, AAAI 2008 Workshop on Intelligent Techniques for Web Personalization and Recommender Systems (ITWP 2008), Exploring Client-Side Instrumentation for Personalized Search Intent Inference: Preliminary Experiments

Exploring Mouse Movements for Inferring Query Intent

Exploring Mouse Movements for Inferring Query Intent (poster) Qi Guo and Eugene Agichtein to appear in the ACM SIGIR International Conference on Research and Development in Information Retrieval (SIGIR), 2008, Exploring Mouse Movements for Inferring Query Intent

Subjectivity Analysis for Questions in QA Communities

Subjectivity Analysis for Questions in QA Communities (poster), Baoli Li, Yandong Liu, Ashwin Ram, Ernest V. Garcia, and Eugene Agichtein, to appear in the ACM SIGIR International Conference on Research and Development in Information Retrieval (SIGIR), 2008, Subjectivity Analysis for Questions in QA Communities

On the Evolution of the Yahoo! Answers QA Community

On the Evolution of the Yahoo! Answers QA Community (poster), Yandong Liu and Eugene Agichtein to appear in the ACM SIGIR International Conference on Research and Development in Information Retrieval (SIGIR), 2008, On the Evolution of the Yahoo! Answers QA Community

A Few Bad Votes Too Many? Towards Robust Ranking in Social Media

A Few Bad Votes Too Many? Towards Robust Ranking in Social Media, Jiang Bian, Yandong Liu, Eugene Agichtein and Hongyuan Zha, to appear in the WWW 2008 workshop on Adversarial Information Retrieval (AIRWeb), 2008, A Few Bad Votes Too Many? Towards Robust Ranking in Social Media

Semantic Annotation and Inference for Medical Knowledge Discovery

Semantic Annotation and Inference for Medical Knowledge Discovery, Saurav Sahay, Eugene Agichtein, Ernest V. Garcia, Baoli Li, and Ashwin Ram, NSF Symposium on Next Generation Data Mining Techniques (NGDM), 2007, Semantic Annotation and Inference for Medical Knowledge Discovery

Discovering Authorities in Question Answer Communities Using Link Analysis

Discovering Authorities in Question Answer Communities Using Link Analysis (short paper), Pawel Jurczyk and Eugene Agichtein, ACM Conference on Information and Knowledge Management (CIKM), 2007, Discovering Authorities in Question Answer Communities Using Link Analysis

HITS on Question Answer Portals: an Exploration of Link Analysis for Author Ranking (poster), Pawel Jurczyk and Eugene Agichtein, ACM SIGIR International Conference on Research and Development in Information Retrieval (SIGIR), 2007

Towards Privacy-Preserving Query Log Publishing

Towards Privacy-Preserving Query Log Publishing (position paper), Li Xiong and Eugene Agichtein, WWW 2007 Workshop on Query Log Analysis: Social and Technological Challenges, 2007, Towards Privacy-Preserving Query Log Publishing

Analysis of Factoid Questions for Effective Relation Extraction (poster), Eugene Agichtein, Silviu Cucerzan, and Eric Brill, ACM SIGIR International Conference on Research and Development in Information Retrieval (SIGIR), 2005

Predicting Extraction Performance by Using Context Language Models

Predicting Extraction Performance by Using Context Language Models, Eugene Agichtein and Silviu Cucerzan, SIGIR 2005 Workshop on Methodologies and Evaluation of Lexical Cohesion Techniques in Real-World Applications., Predicting Extraction Performance by Using Context Language Models

QXtract: A Building Block for Efficient Information Extraction from Plain-Text Databases (demo)

QXtract: A Building Block for Efficient Information Extraction from Plain-Text Databases (demo), Eugene Agichtein and Luis Gravano, ACM International Conference on Management of Data (SIGMOD), 2003, QXtract: A Building Block for Efficient Information Extraction from Plain-Text Databases (demo)

Extracting Relations from XML Documents

Extracting Relations from XML Documents, [ slides ] Eugene Agichtein, C.T. Howard Ho, Vanja Josifovski, and Joerg Gerhardt, Springer Lecture Notes in Computer Science (LNCS), Volume 2814, "Conceptual Modeling for Novel Application Domains; also in the International Workshop on XML Schema and Data Management (XSDM), 2003, Extracting Relations from XML Documents

Snowball: A Prototype System for Extracting Relations from Large Text Collections (demo)

Snowball: A Prototype System for Extracting Relations from Large Text Collections (demo), Eugene Agichtein, Luis Gravano, Jeff Pavel, Viktoriya Sokolova, Alexandr Voskoboynik, ACM International Conference on Management of Data (SIGMOD), 2001, Snowball: A Prototype System for Extracting Relations from Large Text Collections (demo)

Combining Strategies for Extracting Relations from Text Collections

Combining Strategies for Extracting Relations from Text Collections, Eugene Agichtein, Eleazar Eskin and Luis Gravano, ACM SIGMOD Workshop on Data Mining and Knowledge Discovery (DMKD), 2000, Combining Strategies for Extracting Relations from Text Collections

Proceedings of the first CIKM 2008 Workshop on Search in Social Media (SSM 2008), I. Soboroff, E. Agichtein, and R. Kumar (editors)

Combining Lexical and Semantic Features for Recognizing Textual Entailment (RTE4) at TAC 2008, Eugene Agichtein, Walt Askew, and Yandong Liu, to appear in the Proc. of TAC 2008

Domain Ontology Construction from Biomedical Text, Saurav Sahay, Baoli Li, Ernest V. Garcia, Eugene Agichtein, and Ashwin Ram, International Conference on Artificial Intelligence (ICAI), 2007

Extracting Relations From Large Text Collections, Eugene Agichtein, Ph.D. Thesis, Columbia University, 2005

Factoid Question Answering over Unstructured and Structured Content on the Web at TREC 2005

Factoid Question Answering over Unstructured and Structured Content on the Web at TREC 2005, Silviu Cucerzan and Eugene Agichtein, TREC 2005 conference, Factoid Question Answering over Unstructured and Structured Content on the Web at TREC 2005

NYU: Description of the MENE Named Entity System as used in MUC-7

NYU: Description of the MENE Named Entity System as used in MUC-7, Andrew Borthwick, John Sterling, Eugene Agichtein, and Ralph Grishman, 7th Message Understanding Conference (MUC-7) , 1997, NYU: Description of the MENE Named Entity System as used in MUC-7