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Relational peculiarity-oriented mining |
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| Authors: | Muneaki Ohshima Ning Zhong YiYu Yao Chunnian Liu |
| Affiliation: | (1) Department of Information Engineering, Maebashi Institute of Technology, 460-1 Kamisadori-Cho, Maebashi 371-0816, Japan;(2) Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada, S4S 0A2;(3) Computer Science College, Beijing University of Technology, Beijing, 100022, China |
| Abstract: | Peculiarity rules are a new type of useful knowledge that can be discovered by searching the relevance among peculiar data. A main task in mining such knowledge is peculiarity identification. Previous methods for finding peculiar data focus on attribute values. By extending to record-level peculiarity, this paper investigates relational peculiarity-oriented mining. Peculiarity rules are mined, and more importantly explained, in a relational mining framework. Several experiments are carried out and the results show that relational peculiarity-oriented mining is effective. |
| Keywords: | Peculiarity-oriented mining Relational data mining Identification of peculiar records Relational peculiarity rules Multi-database mining |
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