Rerank-by-Example: Efficient Browsing of Web Search Results

  • Takehiro Yamamoto
  • Satoshi Nakamura
  • Katsumi Tanaka
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4653)

Abstract

The conventional Web search has two problems. The first is that users’ search intentions are diverse. The second is that search engines return a huge number of search results which are not ordered correctly. These problems decrease the accuracy of Web searches. To solve these problems, in our past work, we proposed a reranking system based on the user’s search intentions whereby the user edits a part of the search results and the editing operations are propagated to all of the results to rerank them. In this paper, we propose methods of reranking Web search results that depend on the user’s delete and emphasis operations. Then, we describe their evaluation. In addition, we propose a method to support deletion and emphasis by using Tag-Clouds.

Keywords

edit-and-propagate tag-cloud reranking user-interface 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Yamamoto, T., Nakamura, S., Tanaka, K.: An Editable Browser for Reranking Web Search Results. In: Proceedings of the Third International Special Workshop on Databases for Next-Generation Researchers (2007)Google Scholar
  2. 2.
    Broder, A.: A taxonomy of web search. ACM SIGIR Forum 36(2), 3–10 (2002)CrossRefGoogle Scholar
  3. 3.
    Morphological analyzer: ChaSen. http://chasen.naist.jp/hiki/ChaSen/
  4. 4.
  5. 5.
    Kang, I.H., Kim, G.C.: Query type classification for web document retrieval. In: Proceedings of SIGIR 2006, pp. 64–71 (2006)Google Scholar
  6. 6.
    Lee, U., Liu, Z., Cho, J.: Automatic identification of user goals in Web search. In: Proceedings of WWW 2005, pp. 391–400 (2005)Google Scholar
  7. 7.
    Onoda, T., Murata, H., Yamada, S.: Non-Relevance Feedback Document Retrieval Based on One Class SVM and SVDD. In: 2006 IEEE World Congress on Computational Intelligence, pp. 2191–2198 (2006)Google Scholar
  8. 8.
    Rose, D.E., Levinson, D.: Understanding user goals in web search. In: Proceedings of the WWW 2004, pp. 13–19 (2004)Google Scholar
  9. 9.
    Salton, G.: The SMART Retrieval System Experiments in Automatic Document Processing. pp. 312–323 (1971)Google Scholar
  10. 10.
    Salton, G., McGill, M.J.: Introduction to Modern Information Retrieval. McGraw-Hill, New York (1986)Google Scholar
  11. 11.

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Takehiro Yamamoto
    • 1
  • Satoshi Nakamura
    • 1
  • Katsumi Tanaka
    • 1
  1. 1.Department of Social Informatics, Graduate School of Informatics, Kyoto University, Yoshida-Honmachi, Sakyo, Kyoto 606-8501Japan

Personalised recommendations