Associated Pagerank: Improved pagerank measured by frequent term sets
VECIMS（2009）
摘要
Web search engines encounter many new challenges while the amount of information on the Web increases rapidly. Web documents have been a main resource for various purposes, and people rely on search engines to retrieve the desired documents. This paper proposes an associated page rank algorithm for search engines to feedback quality results by scoring the relevance of Web documents. The modified page rank algorithm increases the degree of relevance than the original one, and decreases the query time efforts of topic-sensitive page rank.
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关键词
frequent term set,feedback quality,web search,improved pagerank,main resource,document retrieval,information retrieval,document relevance,topic-sensitive,search engine,web search engine,new challenge,web document,topic-sensitive pagerank,feedback quality result,page rank,modified pagerank algorithm,pagerank,query time effort,search engines,associated pagerank algorithm,data mining,virtual environment,information management,damping,anthropometry,voting,feedback,probability density function,web pages,algorithm design and analysis
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