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Ontological support for association rule mining. (English) Zbl 1157.68413
Gammerman, A. (ed.), Artificial intelligence and applications. Machine learning. As part of the 26th IASTED international multi-conference on applied informatics. Calgary: International Association of Science and Technology for Development (IASTED); Anaheim, CA: Acta Press (ISBN 978-0-88986-710-9/CD-ROM). 110-115 (2008).
Summary: This paper describes some improvements of our previous work that realizes an integrated framework for extracting constraint-based multi-level association rules with an ontology support. The ontology is not the repository of the data, but it models the application domain describing the meta-data. Furthermore, it permits to focus the analysis only on a subset of data and to express multilevel constraints on them. In this context, we report some theoretical notion already introduced and a detailed description of the recent improvements: the introduction of the object properties in the framework, and the implementation of an user interface.
For the entire collection see [Zbl 1154.68012].
MSC:
68T05 Learning and adaptive systems in artificial intelligence
68T10 Pattern recognition, speech recognition
68P05 Data structures
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