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Semantic Data Mining

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The term semantic data mining denotes a data mining approach where domain ontologies are used as background knowledge. Such approach is motivated by large amounts of data that are increasingly becoming openly available and described using real-life ontologies represented in Semantic Web languages. This recently opened up the possibility for interesting large-scale and real-world semantic applications.

The tutorial will address the problems of how machine learning techniques can work directly on the richly structured Semantic Web data, exploit ontologies, and other Semantic Web technologies, what is the value added of machine learning methods exploiting ontologies, and what are the challenges for developers of semantic data mining methods. It will also contain demonstrations of tools supporting semantic data mining.

The tutorial will present the topic of semantic data mining from three complementary perspectives. Firstly, it will present a general framework for semantic data mining, and illustrate it with an example of a new method for semantic subgroup discovery. The second part of tutorial will cover the topic of learning from description logics (DL-learning). Finally, the third part of the tutorial will cover the topic of semantic meta-mining.

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