Flexible queries in relational databases — The example of the division operator

Bosc, Patrick; Dubois, Didier; Pivert, Olivier; Prade, Henri

doi:10.1016/s0304-3975(96)00132-6

Cited by 62 publications

(33 citation statements)

References 20 publications

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“…which is similar to the method presented in Ref. 16 analyzed in Ref. 3 , but they relax the universal quantifier by using both absolute and relative fuzzy quanti-fiers.…”

Section: The Dubois Et Al Divisionmentioning

confidence: 97%

“…Therefore, the most important meanings of these grades may Ž . 7,15,16 be fulfillment degree of a property or condition , membership degree Ž . 8,9,12,17,18 measuring the level of membership of an object to a set , and impor-Ž .…”

Section: žmentioning

confidence: 99%

“…3 there is justification for generalized fuzzy division, a comparison with the classic relational division formula, some possible problems and their solutions, and a comparison with other fuzzy division approaches. 8,12,16 …”

Section: Generalized Fuzzy Relationalmentioning

confidence: 99%

“…Refs. 2 and 3 include a comparison with other fuzzy division approaches that have been published 8,12,16 . We then explain how fuzzy quantifiers may be used to relax the universal quantifier of the division.…”

mentioning

confidence: 99%

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Relaxing the universal quantifier of the division in fuzzy relational databases

Galindo

Medina

Cubero

et al. 2001

Int. J. Intell. Syst.

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In a previous paper, we presented an approach to calculate relational division in fuzzy databases, starting with the GEFRED model. This work centered on dealing with fuzzy attributes and fuzzy values and only the universal quantifier was taken into account since it is the inherent quantifier in classical relational division. In this paper, we present an extension of that division to relax the universal quantifier. With this new system we can use both absolute quantifiers and relative quantifiers irrespective of how the function of the fuzzy quantifier is defined. We also include a comparison with other fuzzy division approaches to relax the universal quantifier that have been published. Furthermore, in this paper we have extended the fuzzy SQL language to express any kind of fuzzy division. ᮊ

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“…which is similar to the method presented in Ref. 16 analyzed in Ref. 3 , but they relax the universal quantifier by using both absolute and relative fuzzy quanti-fiers.…”

Section: The Dubois Et Al Divisionmentioning

confidence: 97%

Section: žmentioning

confidence: 99%

Section: Generalized Fuzzy Relationalmentioning

confidence: 99%

mentioning

confidence: 99%

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Relaxing the universal quantifier of the division in fuzzy relational databases

Galindo

Medina

Cubero

et al. 2001

Int. J. Intell. Syst.

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“…Then the semantics of the division depends on both the choice of the inclusion grade and the intended meaning of the weights associated with the tuples in relations C and Q [14].…”

Section: Division Graded Inclusions and Fuzzy Implicationsmentioning

confidence: 99%

Graded-Inclusion-Based Information Retrieval Systems

Bosc¹,

Claveau²,

Pivert³

et al. 2009

Lecture Notes in Computer Science

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Abstract. This paper investigates the use of fuzzy logic mechanisms coming from the database community, namely graded inclusions, to model the information retrieval process. In this framework, documents and queries are represented by fuzzy sets, which are paired with operations like fuzzy implications and T-norms. Through different experiments, it is shown that only some among the wide range of fuzzy operations are relevant for information retrieval. When appropriate settings are chosen, it is possible to mimic classical systems, thus yielding results rivaling those of state-of-the-art systems. These positive results validate the proposed approach, while negative ones give some insights on the properties needed by such a model. Moreover, this paper shows the added-value of this graded inclusion-based model, which gives new and theoretically grounded ways for a user to easily weight his query terms, to include negative information in his queries, or to expand them with related terms.

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