Top-k Queries with Contextual Fuzzy Preferences

Bosc, Patrick; Pivert, Olivier; Mokhtari, Amine

doi:10.1007/978-3-642-03573-9_72

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Cited by 4 publications

(2 citation statements)

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“…For example, we refer the interested reader to the following works which are not the source papers on the above types of queries but consider them in a fuzzy/possibilistic setting: [13,32,35,72,74,82,94,95,99,105].…”

Section: Tools and Techniquesmentioning

confidence: 99%

Fuzziness in database management systems: Half a century of developments and future prospects

Kacprzyk

Zadrożny

Tré

2015

Fuzzy Sets and Systems

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Section: Tools and Techniquesmentioning

confidence: 99%

Fuzziness in database management systems: Half a century of developments and future prospects

Kacprzyk

Zadrożny

Tré

2015

Fuzzy Sets and Systems

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“…Let us mention that in a work by Bosc et al 28 the term context, which is not related at all to the user context, is used for defining the fuzzy terms "high", "medium" and "low" in a relative way, using the minimal, average and maximal values of the attribute values present in the associated query-defined context. In this work, the context means a referential of values obtained by evaluating a (sub)query over the target database.…”

Section: Related Workmentioning

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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