• DocumentCode
    2563503
  • Title

    Clustering search engine query log containing noisy clickthroughs

  • Author

    Chan, Wing Shun ; Leung, Wai Ting ; Lee, Dik Lun

  • Author_Institution
    Dept. of Comput. Sci., Hong Kong Univ. of Sci. & Technol., Kowloon, China
  • fYear
    2004
  • fDate
    2004
  • Firstpage
    305
  • Lastpage
    308
  • Abstract
    Query clustering is a technique for discovering similar queries on a search engine. In this paper, we present a query clustering method based on the agglomerative clustering algorithm. We first present an overview of the agglomerative clustering algorithm proposed by Beeferman and Berger (2000). We point out a weakness of the method caused by noisy user clicks and propose an improved clustering algorithm. Our results show that in general the agglomerative clustering algorithm can cluster similar queries effectively and that our improved algorithm can successful eliminate noisy clicks and produce cleaner query clusters.
  • Keywords
    Internet; data mining; pattern clustering; query processing; search engines; Internet; agglomerative clustering algorithm; noisy clickthroughs; query clustering; query log clustering; search engines; similar query discovery; Bipartite graph; Clustering algorithms; Clustering methods; Computer science; Internet; Iterative algorithms; Search engines; Web pages;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applications and the Internet, 2004. Proceedings. 2004 International Symposium on
  • Print_ISBN
    0-7695-2068-5
  • Type

    conf

  • DOI
    10.1109/SAINT.2004.1266134
  • Filename
    1266134