Agichtein, Eugene - Department of Mathematics and Computer Science, Emory University

• Improving Web Search Ranking by Incorporating User Behavior Information
• Finding the Right Facts in the Crowd: Factoid Question Answering over Social Media
• Factoid Question Answering over Unstructured and Structured Web Content
• Web Information Extraction and User Modeling: Towards Closing the Gap Eugene Agichtein
• Towards Predicting Web Searcher Gaze Position from Mouse Movements
• Snowball: A Prototype System for Extracting Relations from Large Text Collections
• Modeling Query-Based Access to Text Databases Eugene Agichtein Panagiotis Ipeirotis Luis Gravano
• Predicting Extraction Performance using Context Language Models Eugene Agichtein Silviu Cucerzan
• Combining Strategies for Extracting Relations from Text Collections Eugene Agichtein Eleazar Eskin Luis Gravano
• Exploring Question Subjectivity Prediction in Community QA Baoli Li1 Yandong Liu1 Ashwin Ram2 Ernest V. Garcia1 Eugene Agichtein1
• Predicting Accuracy of Extracting Information from Unstructured Text Collections
• Understanding "Abandoned" Ads: Towards Personalized Commercial Intent Inference via Mouse Movement Analysis
• Query Ambiguity Revisited: Clickthrough Measures for Distinguishing Informational and Ambiguous Queries
• ACM DL 2000 Snowball: Extracting Relations from Large Plain-Text Collections
• Learning to Recognize Reliable Users and Content in Social Media with Coupled Mutual Reinforcement
• Exploring Client-Side Instrumentation for Personalized Search Intent Inference: Preliminary Experiments
• Finding High-Quality Content in Social Media Eugene Agichtein
• To Search or to Crawl? Towards a Query Optimizer for Text-Centric Tasks
• On the Evolution of the Yahoo! Answers QA Community Yandong Liu Eugene Agichtein
• Extracting Relations from Large Text Collections Yevgeny (Eugene) Agichtein
• HITS on Question Answer Portals: Exploration of Link Analysis for Author Ranking
• Discovering Authorities in Question Answer Communities by Using Link Analysis
• Towards a Query Optimizer for Text-Centric Tasks
• QXtract: A Building Block for Efficient Information Extraction from Text Databases
• BIOINFORMATICS Vol. 19 Suppl. 1 2003, pages i340i349 DOI: 10.1093/bioinformatics/btg1047
• Question Answering over Implicitly Structured Web Content Eugene Agichtein
• Exploring Web Browsing Context for Collaborative Question Answering
• Semantic Annotation and Inference for Medical Knowledge Discovery Saurav Sahay
• The Influence of Caption Features on Clickthrough Patterns in Web Search
• Computer Science & Informatics Ph.D. Program The Computer Science and Informatics Ph.D. program
• Querying Text Databases for Efficient Information Extraction Eugene Agichtein Luis Gravano
• Scaling Information Extraction to Large Document Collections Eugene Agichtein
• Learning to Find Answers to Questions on the Web EUGENE AGICHTEIN
• Ready to Buy or Just Browsing? Detecting Web Searcher Goals from Interaction Data
• Deconstructing Interaction Dynamics in Knowledge Sharing Communities
• Predicting Information Seeker Satisfaction in Community Question Answering
• You've Got Answers: Towards Personalized Models for Predicting Success in Community Question Answering
• Identifying "Best Bet" Web Search Results by Mining Past User Behavior
• Confidence Estimation Methods for Partially Supervised Relation Extraction
• Mining Reference Tables for Automatic Text Segmentation Eugene Agichtein
• VPW: An Interactive Prototype of a Web-Based Visual Paired Comparison Cognitive Diagnostic Test
• Characterizing Query Intent From Sponsored Search Clickthrough Data
• Exploring Mouse Movements for Inferring Query Intent Math & Computer Science
• A Few Bad Votes Too Many? Towards Robust Ranking in Social Media
• Extracting Relations from XML Documents Eugene Agichtein1
• Eugene Agichtein KDD Webinar: Towards Web-Scale Information Extraction 1 Towards Web-Scale
• Using the Past To Score the Present: Extending Term Weighting Models Through Revision History Analysis
• CoCQA: Co-Training Over Questions and Answers with an Application to Predicting Question Subjectivity Orientation