Search (2 results, page 1 of 1)

  • × language_ss:"e"
  • × theme_ss:"Data Mining"
  • × theme_ss:"Suchmaschinen"
  1. Baeza-Yates, R.; Hurtado, C.; Mendoza, M.: Improving search engines by query clustering (2007) 0.01 
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    Abstract
    In this paper, we present a framework for clustering Web search engine queries whose aim is to identify groups of queries used to search for similar information on the Web. The framework is based on a novel term vector model of queries that integrates user selections and the content of selected documents extracted from the logs of a search engine. The query representation obtained allows us to treat query clustering similarly to standard document clustering. We study the application of the clustering framework to two problems: relevance ranking boosting and query recommendation. Finally, we evaluate with experiments the effectiveness of our approach.
  2. Vaughan, L.; Chen, Y.: Data mining from web search queries : a comparison of Google trends and Baidu index (2015) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.1, S.13-22

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