A Fuzzy-Rule-Based Approach to Contextual Preference Queries

Hadjali, Allel; Mokhtari, Amine; Pivert, Olivier

doi:10.1007/978-3-642-14049-5_55

Cited by 7 publications

(2 citation statements)

References 10 publications

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“…Our initial work 18 was somewhat inspired by the approach proposed by Stefanidis et al 9,10,19 . Hereafter, we review this approach in a more detailed way and highlight some of its basic shortcomings.…”

Section: Stefanidis Et Al's Approachmentioning

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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Section: Stefanidis Et Al's Approachmentioning

confidence: 99%

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

Hadjali¹,

Mokhtari²,

Pivert³

2012

IJCIS

Self Cite

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“…The term 'context' refers here to any information that can be used to characterize the current query situation [9]. Recently, contextual preferences have received considerable attention in databases and information systems [10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Possibilistic contextual skylines with incomplete preferences

Hadjali

Pivert

Prade³

2010

2010 International Conference of Soft Computing and Pattern Recognition

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We propose a possibility theory-based approach to the treatment of missing user preferences in skyline queries. To compensate this lack of knowledge, we show how a set of plausible preferences suitable for the current context can be derived either in a case-based reasoning manner, or using an extended possibilistic logic setting. Uncertain dominance relationships are defined in a possibilistic way and the notion of possibilistic contextual skyline is introduced. This kind of skyline allows us to return the tuples that are non-dominated with a high certainty. The paper also includes a structured overview of the different types of "fuzzy" skylines.

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