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Enhanced Web search engines with query-concept bipartite graphs

Posted on:2011-08-14Degree:Ph.DType:Thesis
University:Georgia State UniversityCandidate:Chen, YanFull Text:PDF
GTID:2448390002452535Subject:Artificial Intelligence
Abstract/Summary:
With rapid growth of information on the Web, Web search engines have gained great momentum for exploiting valuable Web resources. Although keywords-based Web search engines provide relevant search results in response to users' queries, future enhancement is still needed. Three important issues include (1) search results can be diverse because ambiguous keywords in queries can be interpreted to different meanings (2) identifying keywords in long queries is difficult for search engines and (3) generating query-specific Web page summaries is desirable for Web search results' previews. Based on clickthrough data, this thesis proposes a query-concept bipartite graph for representing queries' relations, and applies the queries' relations to applications such as (1) personalized query suggestions, (2) long queries Web searches and (3) query-specific Web page summarization. Experimental results show that query-concept bipartite graphs are useful for performance improvement for the three applications.Index words. Queries, Query-concept bipartite graph, Web search engine, Text mining, Computational intelligence.
Keywords/Search Tags:Web search, Query-concept bipartite, Queries
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