A new approach for fuzzy information retrieval based on weighted power-mean averaging operators

  • Authors:

  • Won-Sin Hong;Shi-Jay Chen;Li-Hui Wang;Shyi-Ming Chen

  • Affiliations:

  • Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC;Department of Information Management, National United University, Mial-Li, Taiwan, ROC;Department of Finance, Chihlee Institute of Technology, Banciao City, Taipei County, Taiwan, ROC;Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC

  • Venue:
  • Computers & Mathematics with Applications
  • Year:
  • 2007

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Abstract

An information retrieval system can help users to retrieve documents relevant to the users' queries. In recent years, some researchers used averaging operators (i.e., Infinite-One operators, Waller-Kraft operators, P-Norm operators and GMA operators) to handle ''AND'' and ''OR'' operations of users' fuzzy queries for fuzzy information retrieval, but they still have some drawbacks, e.g., sometimes query results do not coincide with the intuition of the human being. In this paper, we present new averaging operators, called weighted power-mean averaging (WPMA) operators, based on the weighted power mean for dealing with fuzzy information retrieval to overcome the drawbacks of the existing methods. Furthermore, we also extend the proposed WPMA operators into the extended WPMA operators to handle weighted fuzzy queries for fuzzy information retrieval. The proposed WPMA operators are more flexible and more intelligent than the existing averaging operators to handle users' fuzzy queries for fuzzy information retrieval.