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Search Result Diversification Based on Query Facets

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Abstract

In search engines, different users may search for different information by issuing the same query. To satisfy more users with limited search results, search result diversification re-ranks the results to cover as many user intents as possible. Most existing intent-aware diversification algorithms recognize user intents as subtopics, each of which is usually a word, a phrase, or a piece of description. In this paper, we leverage query facets to understand user intents in diversification, where each facet contains a group of words or phrases that explain an underlying intent of a query. We generate subtopics based on query facets and propose faceted diversification approaches. Experimental results on the public TREC 2009 dataset show that our faceted approaches outperform state-of-the-art diversification models.

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Authors and Affiliations

  1. School of Information, Renmin University of China, Beijing, 100872, China

    Sha Hu, Zhi-Cheng Dou, Xiao-Jie Wang & Ji-Rong Wen

  2. Key Laboratory of Data Engineering and Knowledge Engineering, Ministry of Education, Beijing, 100872, China

    Sha Hu, Zhi-Cheng Dou, Xiao-Jie Wang & Ji-Rong Wen

Authors
  1. Sha Hu
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  2. Zhi-Cheng Dou
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  3. Xiao-Jie Wang
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  4. Ji-Rong Wen
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Corresponding author

Correspondence to Zhi-Cheng Dou.

Additional information

This work was partially supported by the National Basic Research 973 Program of China under Grant No. 2014CB340403, the Fundamental Research Funds for the Central Universities of China, and the Research Funds of Renmin University of China under Grant No. 15XNLF03.

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Hu, S., Dou, ZC., Wang, XJ. et al. Search Result Diversification Based on Query Facets. J. Comput. Sci. Technol. 30, 888–901 (2015). https://doi.org/10.1007/s11390-015-1567-5

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  • DOI: https://doi.org/10.1007/s11390-015-1567-5

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