An Overview of Fuzzy Approaches to Flexible Database Querying

Zadrożny, Sławomir; Tré, Guy De; Caluwe, Rita M. M. De; Kacprzyk, Janusz

doi:10.4018/978-1-59904-853-6.ch002

Cited by 39 publications

(8 citation statements)

References 54 publications

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“…Preference and flexible queries have attracted a considerable interest in different circles and at different epochs among databases researchers [37,32,35,6,7,21,15,31,14,34,40,41,36]. There may exist slightly different motivations for using flexible queries.…”

Section: Introductionmentioning

confidence: 99%

On various forms of bipolarity in flexible querying

Dubois¹,

Prade²

2013

Proceedings of the 8th Conference of the European Society for Fuzzy Logic and Technology

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The paper discusses the modeling of "if possible" in requirements of the form "A and if possible B". We distinguish between two types of understanding: either i) A and B are requirements of the same nature and are viewed as constraints with different levels of priority, or ii) they are of different nature (only A induces constraint(s) and B is only used for breaking ties among items that are equally satisfying A). We indicate that the two views are related to different types of bipolarity, and discuss them in relation with possibilistic logic. The disjunctive dual of the first view ("A or at least B") is then presented in this logical setting. We also briefly mention the idea of an extension of the second view where B may refer both to bonus conditions or malus conditions that may increase or decrease respectively the interest in an item satisfying A.

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Section: Introductionmentioning

confidence: 99%

On various forms of bipolarity in flexible querying

Dubois¹,

Prade²

2013

Proceedings of the 8th Conference of the European Society for Fuzzy Logic and Technology

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“…A broader discussion of existing fuzzy implications can be found in [22,57,61]. In order to be meaningful, weights should satisfy several requirements [66]. One of them: if w i = 0 then the result should be such as if P i does not exist is briefly examined below.…”

Section: Fuzzy Preferences Between Elementary Query Conditionsmentioning

confidence: 99%

“…The second approach capable to take into account the importance of conditions is based on the OWA operator [66]. The OWA operator [59] is defined by a weight vector W = [w 1 , .…”

Section: Fuzzy Preferences Between Elementary Query Conditionsmentioning

confidence: 99%

“…In order to achieve the mentioned distinction weights w i ∈ [0, 1] can be associated with elementary conditions. Two types of weights can be applied [66]: static and dynamic. Static weights are fixed and known in advance.…”

Section: Fuzzy Preferences Between Elementary Query Conditionsmentioning

confidence: 99%

“…The idea for how to calculate the matching degree of elementary conditions P i according to an importance weight w i has the following form [66]:…”

Section: Fuzzy Preferences Between Elementary Query Conditionsmentioning

confidence: 99%

See 2 more Smart Citations

Some issues of fuzzy querying in relational databases

Hudec¹,

Vučetić²

2016

Kybernetika

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Bipolar database querying using bipolar satisfaction degrees

Matthé

Tré

Zadrożny

et al. 2011

Int. J. Intell. Syst.

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When expressing their information needs in a (database) query, users sometimes prefer to state what has to be rejected rather than what has to be accepted. In general, what has to be rejected is not necessarily the complement of what has to be accepted. This phenomenon is commonly known as the heterogeneous bipolar nature of expressing information needs. Satisfaction degrees in regular fuzzy querying approaches are based on the "symmetric" assumption that the extent to which a database record, respectively, satisfies and does not satisfy a given query are complements of each other and are therefore less suited to adequately handle heterogeneous bipolarity in query specifications and query processing. In this paper, we present a bipolar query satisfaction modeling framework which is based on pairs that consist of an independent degree of satisfaction and degree of dissatisfaction. The use and advantages of the framework are illustrated in the context of fuzzy query evaluation in regular relational databases. More specifically, the evaluation of heterogeneous bipolar queries that contain both positive, negative, and bipolar criteria is studied. C 2011 Wiley Periodicals, Inc.

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An Overview of Fuzzy Approaches to Flexible Database Querying

Cited by 39 publications

References 54 publications

On various forms of bipolarity in flexible querying

On various forms of bipolarity in flexible querying

Some issues of fuzzy querying in relational databases

Bipolar database querying using bipolar satisfaction degrees

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