- Titel
- Joining implications in formal contexts and inductive learning in a Horn description logic
- Untertitel
- Extended Version
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-796143
- Schriftenreihe
- LTCS-Report
- Bandnummer
- 19-02
- Erstveröffentlichung
- 2019
- DOI
- https://doi.org/10.25368/2022.251
- Abstract (EN)
- A joining implication is a restricted form of an implication where it is explicitly specified which attributesmay 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.
- Freie Schlagwörter (DE)
- induktives Lernen, Data Mining, Axiomatik, formale Begriffsanalyse, Implikationsverbindung
- Freie Schlagwörter (EN)
- inductive learning, data mining, axiomatization, formal concept analysis, joining implication
- Klassifikation (DDC)
- 004
- Klassifikation (RVK)
- ST 136
- Publizierende Institution
- Technische Universität Dresden, Dresden
- Version / Begutachtungsstatus
- angenommene Version / Postprint / Autorenversion
- URN Qucosa
- urn:nbn:de:bsz:14-qucosa2-796143
- Veröffentlichungsdatum Qucosa
- 20.06.2022
- Dokumenttyp
- Bericht
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis
CC BY 4.0