Discovering knowledge of association using coherent rules
Mining of association rules is of interest to data miners. Typically, before association rules are mined, a user needs to determine a support threshold in order to obtain only the frequent item sets. Having users to determine a support threshold attracts a number of issues. We propose an associat...
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| Main Authors: | , , , |
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| 格式: | Book Section |
| 出版: |
Springer
2009
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| 主题: | |
| 在线阅读: | http://eprints.utm.my/id/eprint/14462/ |
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| 总结: | Mining of association rules is of interest to data miners. Typically, before
association rules are mined, a user needs to determine a support threshold in order
to obtain only the frequent item sets. Having users to determine a support threshold
attracts a number of issues. We propose an association rule mining framework that
does not require a pre-set support threshold. The framework is developed based on
implication of propositional logic. The experiments show that our approach is able
to identify meaningful association rules. |
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