Anytime classification by ontology approximation

S. Schlobach, E. Blaauw, M. El Kebir, A. Ten Teije, F. Van Harmelen, S. Bortoli, M. Hobbelman, K. Millian, Y. Ren, S. Stam, P. Thomassen, R. Van Het Schip, W. Van Willigem

Research output: Contribution to journalConference articlepeer-review


Reasoning with large or complex ontologies is one of the bottle-necks of the Semantic Web. In this paper we present an anytime algorithm for classification based on approximate subsumption. We give the formal definitions for approximate subsumption, and show its monotonicity and soundness; we show how it can be computed in terms of classical subsumption; and we study the computational behaviour of the algorithm on a set of realistic benchmarks. The most interesting finding is that anytime classification works best on ontologies where classical subsumption is hardest to compute.

Original languageEnglish (US)
JournalCEUR Workshop Proceedings
StatePublished - 2007
Externally publishedYes
Event1st International Workshop on "New Forms of Reasoning for the Semantic Web: Scalable, Tolerant and Dynamic", Co-located with ISWC 2007 and ASWC 2007 - Busan, Korea, Republic of
Duration: Nov 11 2007Nov 11 2007

ASJC Scopus subject areas

  • General Computer Science


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