Asymmetric Composition of Possibilistic Operators in Formal Concept Analysis: Application to the Extraction of Attribute Implications from Incomplete Contexts. Issue 12 (26th May 2017)

• Record Type: Journal Article
• Authors: Ait‐Yakoub, Zina; Djouadi, Yassine; Dubois, Didier; Prade, Henri
• Is Part Of: International journal of intelligent systems. Volume 32:Issue 12(2017)
• Page Start: 1285
• Page End: 1311
• Publication Date: 2017-05-26
• Subjects: Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; 006.3
• DOI: 10.1002/int.21900
• Languages: English
• ISSNs: 0884-8173

Abstract

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.