Readings in Knowledge Representation
Readings in Knowledge Representation
The description logic handbook: theory, implementation, and applications
The description logic handbook: theory, implementation, and applications
Extending OWL by Fuzzy Description Logic
ICTAI '05 Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Fuzzy Ontology, Fuzzy Description Logics and Fuzzy-OWL
WILF '07 Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory
Managing uncertainty and vagueness in description logics for the Semantic Web
Web Semantics: Science, Services and Agents on the World Wide Web
ISWC '08 Proceedings of the 7th International Conference on The Semantic Web
An OWL Ontology for Fuzzy OWL 2
ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
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The problem of concept representation is relevant for knowledge engineering and for ontology-based technologies. However, the notion of concept itself turns out to be highly disputed and problematic in cognitive science. In our opinion, one of the causes of this state of affairs is that the notion of concept is in some sense heterogeneous, and encompasses different cognitive phenomena. This results in a strain between conflicting requirements, such as, for example, compositionality on the one side and the need of representing prototypical information on the other. AI research in some way shows traces of this situation. In this paper we propose an analysis of this state of affairs, and we sketch some proposals for concept representation in formal ontologies which take advantage from suggestions coming from cognitive science and psychological research. In particular we take into account the distinction between prototype and exemplar accounts in explaining prototypical effects.