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Learning Composite Concepts
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology. (IDA/ADIT)ORCID iD: 0000-0002-9084-0470
Linköping University, Department of Computer and Information Science, Database and information techniques.
1998 (English)In: Proceedings of the International Workshop on Description Logics, 1998, 147-152 p.Conference paper (Refereed)
Abstract [en]

This paper proposes a framework to learn concepts from different kinds of observations. We define a language to describe meta-concepts, that represent the sets of possible concepts that can be the result of learning given a set of observations. The kinds of observations that we have studied are subsumption, membership and part-of. We exemplify the framework by showing how composite concepts can be learned in a specific description logic and we show that previous machine learning approaches in description logics can be reformulated in our framework. 1 Introduction In [LM96] the problem of learning composite concepts was formulated in the framework of description logics. Description logics are restricted variants of firstorder logic providing a form of logical bias that dates back to semantic networks. Some recent work investigates concept learning in the context of description logics

Learning Composite Concepts.. Available from: http://www.researchgate.net/publication/220956947_Learning_Composite_Concepts [accessed Jul 1, 2015].

Place, publisher, year, edition, pages
1998. 147-152 p.
National Category
Computer Science
Identifiers
URN: urn:nbn:se:liu:diva-119302OAI: oai:DiVA.org:liu-119302DiVA: diva2:820754
Conference
International Workshop on Description Logics
Available from: 2015-06-12 Created: 2015-06-12 Last updated: 2015-07-01

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ReferencesLink to record
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