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Identifying popular search goals behind search queries to improve web search ranking

Published: 18 December 2011 Publication History

Abstract

Web users usually have a certain search goal before they submit a search query. However, many laypersons can't transform their search goals into suitable queries. Thus, understanding original search goals behind a query is very important for search engines. In the past decade, many researches focus on classifying search goals behind a query into different search-goal categories. In fact, there may be more than one search goal behind a certain query. We thus propose a novel Popular-Search-Goal-based Search Model to effectively identify search goals by the features extracted from search-result snippets and click-through data. Furthermore, we proposed a Search-Goal-based Ranking Model which exploits the identified search goals to re-rank the search result. The experimental result shows our proposed model can effectively identify the search goals behind a search query (achieve precision of 0.94) and enhance the search result ranking (achieve precision of 0.72 for top-1 returned snippet).

References

[1]
Broder, A.: A taxonomy of web search. SIGIR Forum 36(2) (2002).
[2]
Rose, D.E., Levinson, D.: Understanding User Goals in Web Search. In: Proceedings of the 13th International Conference on World Wide Web, pp. 13-19 (2004).
[3]
Kang, I.H., Kim, G.: Query type classification for web document retrieval. In: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (2003).
[4]
Lee, U., Liu, Z., Cho, J.: Automatic Identification of User Goals in Web Search. In: Proceedings of the 14th International Conference on World Wide Web, pp. 391-400 (2005).
[5]
Joachims, T., Granka, L., Pang, B., Hembrooke, H., Gay, G.: Accurately Interpreting Clickthrough Data as Implicit Feedback. In: Proceeding of the ACM SIGIR Conference on Research and Development on Information Retrieval (2005).
[6]
Agichtein, E., Brill, E., Dumais, S.: Improving Web Search Ranking by Incorporating User Behavior. In: Proceedings of the ACM Conference on Research and Development on Information Retrieval (2006).

Cited By

View all
  • (2019)Exploring effective features for recognizing the user intent behind web queriesComputers in Industry10.1016/j.compind.2015.01.00568:C(162-169)Online publication date: 1-Jan-2019
  • (2016)User Intent in Multimedia SearchACM Computing Surveys10.1145/295493049:2(1-37)Online publication date: 13-Aug-2016
  • (2015)Constructing Complex Search Tasks with Coherent Subtask Search GoalsACM Transactions on Asian and Low-Resource Language Information Processing10.1145/274254715:2(1-29)Online publication date: 11-Dec-2015
  1. Identifying popular search goals behind search queries to improve web search ranking

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    Information & Contributors

    Information

    Published In

    cover image Guide Proceedings
    AIRS'11: Proceedings of the 7th Asia conference on Information Retrieval Technology
    December 2011
    625 pages
    ISBN:9783642256301
    • Editors:
    • Mohamed Mohamed Salem,
    • Khaled Shaalan,
    • Farhad Oroumchian,
    • Azadeh Shakery,
    • Halim Khelalfa

    Sponsors

    • Micorsoft Middle East: Micorsoft Middle East
    • Dubai Knowledge Village: Dubai Knowledge Village

    Publisher

    Springer-Verlag

    Berlin, Heidelberg

    Publication History

    Published: 18 December 2011

    Author Tags

    1. information retrieval
    2. language model
    3. search goals
    4. short query
    5. user need
    6. web search

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    View all
    • (2019)Exploring effective features for recognizing the user intent behind web queriesComputers in Industry10.1016/j.compind.2015.01.00568:C(162-169)Online publication date: 1-Jan-2019
    • (2016)User Intent in Multimedia SearchACM Computing Surveys10.1145/295493049:2(1-37)Online publication date: 13-Aug-2016
    • (2015)Constructing Complex Search Tasks with Coherent Subtask Search GoalsACM Transactions on Asian and Low-Resource Language Information Processing10.1145/274254715:2(1-29)Online publication date: 11-Dec-2015

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