Paper Info
Title
Tuning The Matching Function For A Threshold Weighting Semantics In A Linguistic Information Retrieval System
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, Martinez 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" (Heffera-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. (c) 2005 Wiley Periodicals, Inc.
Year
DOI
Venue
2005
10.1002/int.20099
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
Keywords
Field
DocType
linguistic modelling,fuzzy information retrieval,weighted queries.,information retrieval system,information need,information retrieval
Information system,Rule-based machine translation,Data mining,User assistance,Weighting,Information retrieval,Ordinal number,Computer science,Fuzzy logic,User information,Semantics
Journal
Volume
Issue
ISSN
20
9
0884-8173
Citations 
PageRank 
References 
15
0.93
21
Authors
3
Name
Order
Citations
PageRank
Enrique Herrera-Viedma113105642.24
Antonio Gabriel López-herrera242318.65
Carlos Porcel345024.12