Joining Implications in Formal Contexts and Inductive Learning in a Horn Description Logic
Research output: Contribution to book/conference proceedings/anthology/report › Conference contribution › Contributed › peer-review
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 language | English |
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Title of host publication | 15th International Conference on Formal Concept Analysis, ICFCA 2019, Frankfurt, Germany, June 25-28, 2019, Proceedings |
Editors | Diana Cristea, Florence Le Ber, Barş Sertkaya |
Publisher | Springer, Berlin [u. a.] |
Pages | 110-129 |
Number of pages | 20 |
Publication status | Published - 25 Jun 2019 |
Peer-reviewed | Yes |
Publication series
Series | Lecture Notes in Computer Science, Volume 11511 |
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ISSN | 0302-9743 |
External IDs
Scopus | 85068151708 |
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ORCID | /0000-0003-0219-0330/work/153109376 |