Mining association rules with multiple minimum supports using maximum constraints

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چکیده

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Mining association rules with multiple minimum supports using maximum constraints

Data mining is the process of extracting desirable knowledge or interesting patterns from existing databases for specific purposes. Most of the previous approaches set a single minimum support threshold for all the items or itemsets. But in real applications, different items may have different criteria to judge its importance. The support requirements should then vary with different items. In t...

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Mining association rules with multiple minimum supports is an important generalization of the association-rule-mining problem, which was recently proposed by Liu et al. Instead of setting a single minimum support threshold for all items, they allow users to specify multiple minimum supports to reflect the natures of the items, and an Apriori-based algorithm, named MSapriori, is developed to min...

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Most existing algorithms employ a uniform minimum support for mining association rules. Nevertheless, each item in a publication database, even each set of items, is exhibited in an individual period. A reasonable minimum support threshold has to be adjusted according to the exhibition period of each k-itQmsQt Accordingly, this paper proposes a new algorithm, called WMS, for mining association ...

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Mining generalized association rules among items in the presence of taxonomy has been recognized as an important model in data mining. Earlier work on generalized association rules confined the minimum supports to be uniformly specified for all items or items within the same taxonomy level. This constraint would restrain an expert from discovering more interesting but much less supported associ...

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ژورنال

عنوان ژورنال: International Journal of Approximate Reasoning

سال: 2005

ISSN: 0888-613X

DOI: 10.1016/j.ijar.2004.11.006