Joining Implications in Formal Contexts and Inductive Learning in a Horn Description Logic

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Contributors

Abstract

A joining implication is a restricted form of an implication where it is explicitly specified which attributes may occur in the premise and in the conclusion, respectively. A technique for sound and complete axiomatization of joining implications valid in a given formal context is provided. In particular, a canonical base for the joining implications valid in a given formal context is proposed, which enjoys the property of being of minimal cardinality among all such bases. Background knowledge in form of a set of valid joining implications can be incorporated. Furthermore, an application to inductive learning in a Horn description logic is proposed, that is, a procedure for sound and complete axiomatization of Horn-𝓜 concept inclusions from a given interpretation is developed. A complexity analysis shows that this procedure runs in deterministic exponential time.

Details

Original languageEnglish
Title of host publication15th International Conference on Formal Concept Analysis, ICFCA 2019, Frankfurt, Germany, June 25-28, 2019, Proceedings
EditorsDiana Cristea, Florence Le Ber, Barş Sertkaya
PublisherSpringer, Berlin [u. a.]
Pages110-129
Number of pages20
Publication statusPublished - 25 Jun 2019
Peer-reviewedYes

Publication series

SeriesLecture Notes in Computer Science, Volume 11511
ISSN0302-9743

External IDs

Scopus 85068151708
ORCID /0000-0003-0219-0330/work/153109376

Keywords

Library keywords