Search (2 results, page 1 of 1)

  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  • × theme_ss:"Suchmaschinen"
  • × year_i:[2000 TO 2010}
  1. Pahlevi, S.M.; Kitagawa, H.: Conveying taxonomy context for topic-focused Web search (2005) 0.00 
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    Abstract
    Introducing context to a user query is effective to improve the search effectiveness. In this article we propose a method employing the taxonomy-based search services such as Web directories to facilitate searches in any Web search interfaces that support Boolean queries. The proposed method enables one to convey current search context an taxonomy of a taxonomy-based search service to the searches conducted with the Web search interfaces. The basic idea is to learn the search context in the form of a Boolean condition that is commonly accepted by many Web search interfaces, and to use the condition to modify the user query before forwarding it to the Web search interfaces. To guarantee that the modified query can always be processed by the Web search interfaces and to make the method adaptive to different user requirements an search result effectiveness, we have developed new fast classification learning algorithms.
    Type
    a
  2. Scholer, F.; Williams, H.E.; Turpin, A.: Query association surrogates for Web search (2004) 0.00 
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    Abstract
    Collection sizes, query rates, and the number of users of Web search engines are increasing. Therefore, there is continued demand for innovation in providing search services that meet user information needs. In this article, we propose new techniques to add additional terms to documents with the goal of providing more accurate searches. Our techniques are based an query association, where queries are stored with documents that are highly similar statistically. We show that adding query associations to documents improves the accuracy of Web topic finding searches by up to 7%, and provides an excellent complement to existing supplement techniques for site finding. We conclude that using document surrogates derived from query association is a valuable new technique for accurate Web searching.
    Type
    a

Authors