Fuzzy sets in database and information systems: Status and opportunities

Bosc, Patrick; Kraft, Donald H.; Petry, Frederick E.

doi:10.1016/j.fss.2005.05.039

Cited by 70 publications

(30 citation statements)

References 43 publications

(38 reference statements)

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“…Several fuzzy query implementations have been proposed such as [13,28,31,40,41,46] and [55]. A consistent survey of the status and opportunities of fuzzy sets in all areas of databases and information systems including fuzzy queries can be found in [6]. A detailed description of fuzzy queries can be found in [44] where authors examined queries on crisp and fuzzy databases.…”

Section: Doi: 1014736/kyb-2015-6-0994mentioning

confidence: 99%

Some issues of fuzzy querying in relational databases

Hudec¹,

Vučetić²

2016

Kybernetika

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Section: Doi: 1014736/kyb-2015-6-0994mentioning

confidence: 99%

Some issues of fuzzy querying in relational databases

Hudec¹,

Vučetić²

2016

Kybernetika

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“…In particular, a distinction can be made between mandatory and desired query conditions. These conditions can still contain vague terms modelled by fuzzy sets as in regular 'fuzzy' querying [38,22,5,7,21,4,46]. For example, in [48] an approach is presented where bipolar queries are represented as a special case of the fuzzy 'winnow' operator.…”

Section: Bipolar Query Conditionsmentioning

confidence: 99%

“…Indeed, the main lines of research in this area include the study of modeling linguistic terms (like, e.g., young or high) in the specification of elementary query conditions using elements of fuzzy logic [38] and the enhancement of fuzzy query formalism with soft aggregation operators [23,22,6,15]. Both linguistic terms and soft aggregations model user's preferences [4] and, as such, require a query satisfaction modeling framework that supports rank-ordering the records retrieved in response to a query according to the degree to which they satisfy all conditions imposed by the query. Usually, query satisfaction in 'fuzzy' querying of regular databases is modelled by associating a satisfaction degree s with each record in the answer set of the query.…”

Section: Introductionmentioning

confidence: 99%

Constraint-Wish and Satisfied-Dissatisfied: An Overview of Two Approaches for Dealing with Bipolar Querying

Matthé

Nielandt

Zadrożny

et al. 2013

Flexible Approaches in Data, Information and Knowledge Management

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In recent years, there has been an increasing interest in dealing with user preferences in flexible database querying, expressing both positive and negative information in a heterogeneous way. This is what is usually referred to as bipolar database querying. Different frameworks have been introduced to deal with such bipolarity. In this chapter, an overview of two approaches is given. The first approach is based on mandatory and desired requirements. Hereby the complement of a mandatory requirement can be considered as a specification of what is not desired at all. So, mandatory requirements indirectly contribute to negative information (expressing what the user does not want to retrieve), whereas desired requirements can be seen as positive information (expressing what the user prefers to retrieve). The second approach is directly based on positive requirements (expressing what the user wants to retrieve), and negative requirements (expressing what the user does not want to retrieve). Both approaches use pairs of satisfaction degrees as the underlying framework but have different semantics, and thus also different operators for criteria evaluation, ranking, aggregation, etc.

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“…Fuzzy (or flexible) queries 14,15 are requests that involve gradual predicates (such as young and wellpaid) modeled by means of fuzzy sets. Thanks to the notion of fuzzy set membership functions, such predicates constitute a convenient and suitable tool for expressing user's preferences.…”

Section: Fuzzy Queriesmentioning

confidence: 99%

A Fuzzy-Rule-Based Model for Handling Contextual Preference Queries

Hadjali¹,

Mokhtari²,

Pivert³

2012

IJCIS

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Users' preferences have traditionally been exploited in query personalization to better serve their information needs. Most of the time, user preferences depend on context, that is, they may have different values depending on the situation of the user. In this paper, we propose a fuzzy-rule-based model for the representation of contextual preferences in a database querying framework. We discuss the augmentation of a query with preferences deduced from information regarding the current context of the user. To this end, we make use of an appropriate inference pattern, called generalized modus ponens, able to deal with data and knowledge when they are described in a fuzzy way.

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Fuzzy sets in database and information systems: Status and opportunities

Cited by 70 publications

References 43 publications

Some issues of fuzzy querying in relational databases

Some issues of fuzzy querying in relational databases

Constraint-Wish and Satisfied-Dissatisfied: An Overview of Two Approaches for Dealing with Bipolar Querying

A Fuzzy-Rule-Based Model for Handling Contextual Preference Queries

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