Relational Peculiarity Oriented Data Mining

Authors:
Ning Zhong;Chunnian Liu;Y. Y. Yao;Muneaki Ohshima;Mingxin Huang;Jiajin Huang
Affiliations:
Maebashi Institute of Technology, Japan;Beijing University of Technology, China;University of Regina, Canada;Maebashi Institute of Technology, Japan;Beijing University of Technology, China;Beijing University of Technology, China
Venue:
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Year:
2004

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Abstract

Peculiarity rules are a new type of interesting rules which can be discovered by searching the relevance among peculiar data. A main task of mining peculiarity rules is the identification of peculiarity. Traditional methods of finding peculiar data are attribute-based approaches. This paper extends peculiarity oriented mining to relational peculiarity oriented mining. Peculiar data are identified on record level, and peculiar rules are mined and explained in a relational mining framework. The results from preliminary experiments show that relational peculiarity oriented mining is very effective.