A fuzzy linguistic approach generalizing Boolean Information Retrieval: A model and its evaluation

• Published in: Journal of the American Society for Information Science Vol. 44; no. 2; pp. 70 - 82
• Main Authors: Bordogna, Gloria, Pasi, Gabriella
• Format: Journal Article
• Language: English
• Published: Washington, D.C Wiley Subscription Services, Inc., A Wiley Company 01.03.1993; John Wiley & Sons; American Documentation Institute; Wiley Periodicals Inc
• Subjects: Boolean; Boolean algebra; Boolean Search Strategy; Boolean strategies; Classification; Evaluation Methods; Exact sciences and technology; Fuzzy Concepts; Fuzzy set theory; Fuzzy sets; Generalization; Information and communication sciences; Information processing and retrieval; Information Retrieval; Information retrieval systems. Information and document management system; Information science. Documentation; Linguistics; Mathematical Models; Queries; Query languages; Relevance; Relevance (Information Retrieval); Sciences and techniques of general use; Searching; Semantics; Set theory; Subject indexes; Subjectivity; Theoretical linguistics; Translating; Translation; User needs; Weighted Term Searching; System evaluation; Uncertainty; Variable; Query; Fuzzy set; Implementation; Document retrieval; Boolean model; Fuzzy query; Weighting; Document retrieval system; Semantics; Quantizer; Linguistics; Extended boolean model; Natural language; Models; Combined treatment
• ISSN: 0002-8231; 1097-4571
• DOI: 10.1002/(SICI)1097-4571(199303)44:2<70::AID-ASI2>3.0.CO;2-I

The generalization of Boolean Information Retrieval Systems (IRS) is still an open research field; in fact, though such systems are diffused on the market, they present some limitations; one of the main features lacking in these systems is the ability to deal with the “imprecision” and “subjectivity” characterizing retrieval activity. However, the replacement of such systems would be much more costly than their evolution through the incorporation of new features to enhance their efficiency and effectiveness. Previous efforts in this area have led to the introduction of numeric weights to improve both document representation and query language. By attaching a numeric weight to a term in a query, a user can provide a quantitative description of the “importance” of that term in the documents he or she is looking for. However, the use of weights requires a clear knowledge of their semantics for translating a fuzzy concept into a precise numeric value. Our acquaintance with these problems led us to define, starting from an existing weighted Boolean retrieval model, a linguistic extension, formalized within fuzzy set theory, in which numeric query weights are replaced by linguistic descriptors which specify the degree of importance of the terms. This fuzzy linguistic model is defined and an evaluation is made of its implementation on a Boolean IRS. © 1993 John Wiley & Sons, Inc.