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Inductive Query Answering and Concept Retrieval Exploiting Local Models

Abstract:

We present a classification method, founded in the instance-based learning and the disjunctive version space approach, for performing approximate retrieval from knowledge bases expressed in Description Logics. It is able to supply answers, even though they are not logically entailed by the knowledge base (e.g. because of its incompleteness or when there are inconsistent assertions). Moreover, the method may also induce new knowledge that can be employed to make the ontology population task semi-automatic. The method has been experimentally tested showing that it is sound and effective.

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Publisher:
IEEE
Host title:
Proceedings of the 9th International Conference on Intelligent Systems Design and Applications‚ ISDA 2009‚ Pisa‚ Italy‚ November 30−December 2‚ 2009
Publication date:
2009-01-01
ISBN:
9780769538723


UUID:
uuid:1a70ecf7-103e-4576-8e25-eba87c21fe63
Local pid:
cs:6615
Deposit date:
2015-03-31
ARK identifier:

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