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Asymmetric Composition of Possibilistic Operators in Formal Concept Analysis: Application to the Extraction of Attribute Implications from Incomplete Contexts.

Ait-Yakoub, Zina and Djouadi, Yassine and Dubois, Didier and Prade, Henri Asymmetric Composition of Possibilistic Operators in Formal Concept Analysis: Application to the Extraction of Attribute Implications from Incomplete Contexts. (2017) International Journal of Intelligent Systems, 32 (12). 1285-1311. ISSN 0884-8173

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Official URL: https://doi.org/10.1002/int.21900

Abstract

Formal concept analysis theory (FCA) classically relies on the use of the Galois powerset operator. Formal similarities between possibility theory and formal concept analysis have led to the use of possibilistic operators in FCA, which were ignored before. In this paper, an approach based on the use of asymmetric composition of the two most usual possibilistic operators is proposed. It enables us to complement the stem base, by deriving attribute implications with disjunctions on both sides of the implications. Besides, the approach is also generalized to incomplete contexts involving explicit positive and negative information. We outline the potential application of these results to the completion of TBoxes in description logic.

Item Type:Article
HAL Id:hal-02552195
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Other partners > Université des Sciences et de la Technologie Houari Boumediene - USTHB (ALGERIA)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Other partners > Université Mouloud Mammeri Tizi Ouzou - UMMTO (ALGERIA)
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Deposited On:23 Apr 2020 11:10

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