Document Type
Conference Proceeding
Publication Date
1-1-2010
Abstract
With the development of more expressive description logics (DLs) for the Web Ontology Language OWL the question arises how we can properly deal with the high computational complexity for efficient reasoning. In application cases that require scalable reasoning with expressive ontologies, non-standard reasoning solutions such as approximate reasoning are necessary to tackle the intractability of reasoning in expressive DLs. In this paper, we are concerned with the approximation of the reasoning task of instance retrieval on DL knowledge bases, trading correctness of retrieval results for gain of speed. We introduce our notion of an approximate concept extension and we provide implementations to compute an approximate answer for a concept query by a suitable mapping to efficient database operations. Furthermore, we report on experiments of our approach on instance retrieval with the Wine ontology and discuss first results in terms of error rate and speed-up.
Repository Citation
Tserendorj, T.,
Grimm, S.,
& Hitzler, P.
(2010). Approximate Instance Retrieval on Ontologies. Lecture Notes in Computer Science, 6261, 503-511.
https://corescholar.libraries.wright.edu/cse/136
DOI
10.1007/978-3-642-15364-8_43
Included in
Bioinformatics Commons, Communication Technology and New Media Commons, Databases and Information Systems Commons, OS and Networks Commons, Science and Technology Studies Commons
Comments
Presented at the 21st International Conference on Database and Expert Systems Applications, Bilbao, Spain, August 30-September 3, 2010.
Attached is the unpublished, authors' version of this proceeding. The final, publisher's version can be found at http://dx.doi.org/10.1007/978-3-642-15364-8_43.