Improving Category Specific Web Search By Learning Query Modifications
SAINT '01: Proceedings of the 2001 Symposium on Applications and the Internet (SAINT 2001)(2001)
摘要
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.
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关键词
Internet,classification,hypermedia markup languages,information resources,information retrieval,learning (artificial intelligence),search engines,HTML,Inquirus,Internet,Web search engines,category specific Web search,classification,documents,home pages,information retrieval,query modification learning,text location,textual content,
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