Multi-relational Association Rule Mining with Guidance of User

Authors:
Jingfeng Guo;Weifeng Bian;Jing Li
Affiliations:
Yanshan University;Yanshan University;Yanshan University
Venue:
FSKD '07 Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02
Year:
2007

Citing 0
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Genetic algorithm-based optimized association rule mining for multi-relational data

Intelligent Data Analysis

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Abstract

1 A multi-relational association rule mining algorithm with guidance of the user is proposed in this paper. A tuple ID propagation approach is used to solve the association rule mining with multiple database relations directly, and introduces the concept of the user's guidance in this paper. The approach has improved user's satisfaction with the mining result. Compared with the traditional algorithms, it improves the accuracy and supports multi-relational databases directly, so its running time is less than that of the multi-relational association rule mining methods based on ILP.