Details

Autor(en) / Beteiligte

• Divroodi, Ali Rezaei
• Ha, Quang-Thuy
• Nguyen, Linh Anh
• Nguyen, Hung Son

Titel

On the possibility of correct concept learning in description logics

Ist Teil von

• Vietnam journal of computer science, 2018-02, Vol.5 (1), p.3-14

Ort / Verlag

Berlin/Heidelberg: Springer Berlin Heidelberg

Erscheinungsjahr

2018

Link zum Volltext

Quelle

Electronic Journals Library - Freely accessible e-journals

Beschreibungen/Notizen

• It is well known that any Boolean function in classical propositional calculus can be learned correctly if the training information system is good enough. In this paper, we extend that result for description logics. We prove that any concept in any description logic that extends ALC with some features amongst I (inverse roles), Q k (qualified number restrictions with numbers bounded by a constant k ), and Self (local reflexivity of a role) can be learned correctly if the training information system (specified as a finite interpretation) is good enough. That is, there exists a learning algorithm such that, for every concept C of those logics, there exists a training information system such that applying the learning algorithm to it results in a concept equivalent to  C . For this result, we introduce universal interpretations and bounded bisimulation in description logics and develop an appropriate learning algorithm. We also generalize common types of queries for description logics, introduce interpretation queries, and present some consequences.