Document Type
Conference Proceeding
Publication Date
6-1-2007
Abstract
With the advent of the Semantic Web, description logics have become one of the most prominent paradigms for knowledge representation and reasoning. Progress in research and applications, however, faces a bottleneck due to the lack of available knowledge bases, and it is paramount that suitable automated methods for their acquisition will be developed. In this paper, we provide the first learning algorithm based on refinement operators for the most fundamental description logic ALC. We develop the algorithm from thorough theoretical foundations and report on a prototype implementation.
Repository Citation
Lehmann, J.,
& Hitzler, P.
(2007). A Refinement Operator Based Learning Algorithm for the ALC Description Logic. Lecture Notes in Computer Science, 147-160.
https://corescholar.libraries.wright.edu/cse/94
DOI
10.1007/978-3-540-78469-2_17
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 17th International Conference on Inductive Logic Programming, Corvallis, OR, June 19-21, 2007.
Attached is the unpublished, authors' version of this proceeding. The final, publisher's version can be at http://dx.doi.org/10.1007/978-3-540-78469-2_17.