Mining the web to create minority language corpora
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Extracting query modifications from nonlinear SVMs
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Probabilistic question answering on the web
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Using web structure for classifying and describing web pages
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Personalized web search by mapping user queries to categories
Proceedings of the eleventh international conference on Information and knowledge management
Text Retrieval Systems for the Web
Programming and Computing Software
Online Learning for Web Query Generation: Finding Documents Matching a Minority Concept on the Web
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CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
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Information Processing and Management: an International Journal
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SS '10 Proceedings of the NAACL HLT 2010 Workshop on Semantic Search
Modeling information incorporation in markets, with application to detecting and explaining events
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Clustering scientific literature using sparse citation graph analysis
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Retrieval of Web Pages on Real-World Events related to Physical Objects
International Journal of Information Retrieval Research
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Abstract Users looking for documents within specific categories may have a difficult time locating valuable documents using general purpose search engines. We present an automated method for learning query modifications that can dramatically improve precision for locating pages within specified categories using web search engines. We also present a classification procedure that can recognize pages in a specific category with high precision, using textual content, text location, and HTML structure. Evaluation shows that the approach is highly effective for locating personal homepages and calls for papers. These algorithms are used to improve category specific search in the Inquirus 2 search engine.