Recognition and classification of noun phrases in queries for effective retrieval

  • Authors:
  • Wei Zhang;Shuang Liu;Clement Yu;Chaojing Sun;Fang Liu;Weiyi Meng

  • Affiliations:
  • University of Illinois at Chicago, Chicago, IL;Ask.com, Edison, NJ;University of Illinois at Chicago, Chicago, IL;Broadcom Corporation, San Diego, CA;Microsoft, Redmond, WA;Binghamton University, Binghamton, NY

  • Venue:
  • Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
  • Year:
  • 2007

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Abstract

It has been shown that using phrases properly in the document retrieval leads to higher retrieval effectiveness. In this paper, we define four types of noun phrases and present an algorithm for recognizing these phrases in queries. The strengths of several existing tools are combined for phrase recognition. Our algorithm is tested using a set of 500 web queries from a query log, and a set of 238 TREC queries. Experimental results show that our algorithm yields high phrase recognition accuracy. We also use a baseline noun phrase recognition algorithm to recognize phrases from the TREC queries. A document retrieval experiment is conducted using the TREC queries (1) without any phrases, (2) with the phrases recognized from a baseline noun phrase recognition algorithm, and (3) with the phrases recognized from our algorithm respectively. The retrieval effectiveness of (3) is better than that of (2), which is better than that of (1). This demonstrates that utilizing phrases in queries does improve the retrieval effectiveness, and better noun phrase recognition yields higher retrieval performance.