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Published in:
2005 | OriginalPaper | Chapter
Database Support for Data Mining Patterns
Authors : Evangelos Kotsifakos, Irene Ntoutsi, Yannis Theodoridis
Published in: Advances in Informatics
Publisher: Springer Berlin Heidelberg
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The need of extracting useful knowledge from large collections of data has led to a great development of data mining systems and techniques. The results of data mining are known as patterns. Patterns can also be found in other scientific areas, such as biology, astronomy, mathematics etc. Today requirements impose the need for a system that efficiently manipulates complex and diverse patterns. In this work, we study the problem of the efficient representation and storage of patterns in a so-called pattern-base Management System. Towards this aim we examine three well known models from the database domain, the relational, the object-relational and the semi-structured (XML) model. The three alternative models are presented and compared based on criteria like generality, extensibility and querying effectiveness. The comparison shows that the semi-structure representation is more appropriate for a pattern-base.