Tuning the matching function for a threshold weighting semantics in a linguistic information retrieval system: Research Articles

Authors:
E. Herrera-Viedma;A. G. López-Herrera;C. Porcel
Affiliations:
Department of Computer Science and Artificial Intelligence, Library Science Studies School, University of Granada, 18071, Granada, Spain;Department of Computer Science and Artificial Intelligence, Library Science Studies School, University of Granada, 18071, Granada, Spain;Department of Computer Science and Artificial Intelligence, Library Science Studies School, University of Granada, 18071, Granada, Spain
Venue:
International Journal of Intelligent Systems
Year:
2005

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Abstract

Information retrieval is an activity that attempts to produce documents that better fulfill user information needs. To achieve this activity an information retrieval system uses matching functions that specify the degree of relevance of a document with respect to a user query. Assuming linguistic-weighted queries we present a new linguistic matching function for a threshold weighting semantics that is defined using a 2-tuple fuzzy linguistic approach (Herrera F, Martínez L. IEEE Trans Fuzzy Syst 2000;8:746–752). This new 2-tuple linguistic matching function can be interpreted as a tuning of that defined in “Modelling the Retrieval Process for an Information Retrieval System Using an Ordinal Fuzzy Linguistic Approach” (Herrera-Viedma E. J Am Soc Inform Sci Technol 2001;52:460–475). We show that it simplifies the processes of computing in the retrieval activity, avoids the loss of precision in final results, and, consequently, can help to improve the users' satisfaction. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 921–937, 2005.