Pattern Discovery in Triadic Contexts

Missaoui, Rokia; Ruas, Pedro H. B.; Kwuida, Léonard; Song, Mark A. J. (2020). Pattern Discovery in Triadic Contexts In: International Conference on Conceptual Structures ICCS 2020: Ontologies and Concepts in Mind and Machine. Lecture Notes in Computer Science: Vol. 12277 (pp. 117-131). Springer 10.1007/978-3-030-57855-8_9

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Many real-life applications are best represented as ternary and more generally n-ary relations. In this paper, we use Triadic Concept Analysis as a framework to mainly discover implications. Indeed, our contributions are as follows. First, we adapt the iPred algorithm for precedence link computation in concept lattices to the triadic framework. Then, new algorithms are proposed to compute triadic generators by extending the notion of faces and blockers to further calculate implications.

Item Type:	Conference or Workshop Item (Paper)
Division/Institute:	Business School > Business Foundations and Methods
Name:	Missaoui, Rokia; Ruas, Pedro H. B.; Kwuida, Léonard0000-0002-9811-0747 and Song, Mark A. J.
ISBN:	978-3-030-57854-1
Series:	Lecture Notes in Computer Science
Publisher:	Springer
Language:	English
Submitter:	Léonard Kwuida
Date Deposited:	01 Oct 2020 13:55
Last Modified:	21 Sep 2021 02:18
Publisher DOI:	10.1007/978-3-030-57855-8_9
Uncontrolled Keywords:	Triadic concepts · Triadic generators · Implication rules
ARBOR DOI:	10.24451/arbor.12971
URI:	https://arbor.bfh.ch/id/eprint/12971