Efficiently mining both association and correlation rules

被引:0
|
作者
Zhou, Zhongmei [1 ]
Wu, Zhaohui [1 ]
Wang, Chunshan [1 ]
Feng, Yi [1 ]
机构
[1] Zhejiang Univ, Coll Comp Sci & Technol, Zhengzhou, Peoples R China
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D O I
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中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Associated and correlated patterns cannot fully reflect association and correlation relationships between items like both association and correlation rules. Moreover, both association and correlation rule mining can find such type of rules, "the conditional probability that a customer purchasing A is likely to also purchase B is not only greater than the given threshold, but also significantly greater than the probability that a customer purchases only B. In other words, the sale of A can increase the likelihood of the sale of B." Therefore, in this paper, we combine association with correlation in the mining process to discover both association and correlation rules. A new notion of a both association and correlation rule is given and an algorithm is developed for discovering all both association and correlation rules. Our experimental results show that the mining combined association with correlation is quite a good approach to discovering both association and correlation rules.
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页码:369 / 372
页数:4
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