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

Bordogna, G., & Pasi, G. (1993). A Fuzzy Linguistic Approach Generalizing Boolean Information Retrieval: a Model and its Evaluation. JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE, 44(2), 70-82 [10.1002/(SICI)1097-4571(199303)44:2<70::AID-ASI2>3.0.CO;2-I].

A Fuzzy Linguistic Approach Generalizing Boolean Information Retrieval: a Model and its Evaluation

PASI, GABRIELLA
1993

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
No
Articolo in rivista - Articolo scientifico
Scientifica
Information Retrieval, Models, Fuzzy Set Theory
English
70
82
13
Bordogna, G., & Pasi, G. (1993). A Fuzzy Linguistic Approach Generalizing Boolean Information Retrieval: a Model and its Evaluation. JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE, 44(2), 70-82 [10.1002/(SICI)1097-4571(199303)44:2<70::AID-ASI2>3.0.CO;2-I].
Bordogna, G; Pasi, G
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10281/43395
Citazioni
  • Scopus 196
  • ???jsp.display-item.citation.isi??? 169
Social impact