Abstract
This paper contains the experimental investigation of an approach, named SEMINTEC, to frequent pattern mining in combined knowledge bases represented in description logic with rules (so-called \({\mathcal DL}\)-safe ones). Frequent patterns in this approach are the conjunctive queries to a combined knowledge base. In this paper, first, we prove that the approach introduced in our previous work for the DLP fragment of description logic family of languages, is also valid for more expressive languages. Next, we present the experimental results under different settings of the approach, and on knowledge bases of different sizes and complexities.
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Józefowska, J., Ławrynowicz, A., Łukaszewski, T. (2009). A Study of the SEMINTEC Approach to Frequent Pattern Mining. In: Berendt, B., et al. Knowledge Discovery Enhanced with Semantic and Social Information. Studies in Computational Intelligence, vol 220. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01891-6_3
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DOI: https://doi.org/10.1007/978-3-642-01891-6_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01890-9
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