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Published in:
2009 | OriginalPaper | Chapter
Semantic Analytical Reports: A Framework for Post-processing Data Mining Results
Authors : Tomáš Kliegr, Martin Ralbovský, Vojtěch Svátek, Milan Šimůnek, Vojtěch Jirkovský, Jan Nemrava, Jan Zemánek
Published in: Foundations of Intelligent Systems
Publisher: Springer Berlin Heidelberg
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Intelligent post-processing of data mining results can provide valuable knowledge. In this paper we present the first systematic solution to post-processing that is based on semantic web technologies. The framework input is constituted by PMML and description of background knowledge. Using the Topic Maps formalism, a generic Data Mining ontology and Association Rule Mining ontology were designed. Through combination of a content management system and a semantic knowledge base, the analyst can enter new pieces of information or interlink existing ones. The information is accessible either via semi-automatically authored textual analytical reports or via semantic querying. A prototype implementation of the framework for generalized association rules is demonstrated on the PKDD’99 Financial Data Set.