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Identifying vertical search intention of query through social tagging propagation

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Published:20 April 2009Publication History

ABSTRACT

A pressing task during the unification process is to identify a user's vertical search intention based on the user's query. In this paper, we propose a novel method to propagate social annotation, which includes user-supplied tag data, to both queries and VSEs for semantically bridging them. Our proposed algorithm consists of three key steps: query annotation, vertical annotation and query intention identification. Our algorithm, referred to as TagQV, verifies that the social tagging can be propagated to represent Web objects such as queries and VSEs besides Web pages. Experiments on real Web search queries demonstrate the effectiveness of TagQV in query intention identification.

References

  1. Meng, W.Y., Yu, C. and Liu, K.L. Building efficient and effective metasearch engines. ACM Computing Surveys (March 2002), 34(1), 48--89. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Shen, D., Pan, R., Sun, J.T., Pan, J.J., Wu, K.H., Yin, J. and Yang, Q. Query enrichment for web-query classification. ACM TOIS (July 2006), 24 (3), 320--352. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Yang, Y.M. An Evaluation of Statistical Approaches to Text Categorization. Journal of Information Retrieval (1999), 1 (1/2), 67--88. Google ScholarGoogle ScholarDigital LibraryDigital Library

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