Joining Implications in Formal Contexts and Inductive Learning in a Horn Description Logic
Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/Gutachten › Beitrag in Konferenzband › Beigetragen › Begutachtung
Beitragende
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
Originalsprache | Englisch |
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Titel | 15th International Conference on Formal Concept Analysis, ICFCA 2019, Frankfurt, Germany, June 25-28, 2019, Proceedings |
Redakteure/-innen | Diana Cristea, Florence Le Ber, Barş Sertkaya |
Herausgeber (Verlag) | Springer, Berlin [u. a.] |
Seiten | 110-129 |
Seitenumfang | 20 |
Publikationsstatus | Veröffentlicht - 25 Juni 2019 |
Peer-Review-Status | Ja |
Publikationsreihe
Reihe | Lecture Notes in Computer Science, Volume 11511 |
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ISSN | 0302-9743 |
Externe IDs
Scopus | 85068151708 |
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ORCID | /0000-0003-0219-0330/work/153109376 |