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

TLDR

Boolean information retrieval systems lack mechanisms to handle imprecision and subjectivity, and replacing them would be costly, so researchers have added numeric weights to improve representation and query language. The study proposes a linguistic extension of a weighted Boolean retrieval model, replacing numeric query weights with fuzzy linguistic descriptors that indicate term importance. The authors formalize this extension within fuzzy set theory, defining a model that assigns linguistic importance levels to query terms and evaluate its implementation on a Boolean IRS. Evaluation of the fuzzy linguistic model on a Boolean IRS demonstrates its feasibility and potential to enhance retrieval effectiveness. © 1993 John Wiley & Sons, Inc.

Abstract

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.