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Published in:
2012 | OriginalPaper | Chapter
An Approach to Parallel Class Expression Learning
Authors : An C. Tran, Jens Dietrich, Hans W. Guesgen, Stephen Marsland
Published in: Rules on the Web: Research and Applications
Publisher: Springer Berlin Heidelberg
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We propose a Parallel Class Expression Learning algorithm that is inspired by the OWL Class Expression Learner (OCEL) and its extension – Class Expression Learning for Ontology Engineering (CELOE) – proposed by Lehmann et al. in the DL-Learner framework. Our algorithm separates the computation of
partial definitions
from the aggregation of those solutions to an overall
complete definition
, which lends itself to parallelisation. Our algorithm is implemented based on the DL-Learner infrastructure and evaluated using a selection of datasets that have been used in other ILP systems. It is shown that the proposed algorithm is suitable for learning problems that can only be solved by complex (long) definitions. Our approach is part of an ontology-based abnormality detection framework that is developed to be used in smart homes.