【摘 要】
:
Indirect association is a high level relationship between items and frequent itemsets in data. Current research approaches on indirect association mining are li
【机 构】
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Department of Computer Science and Engineering
【基金项目】
:
国家自然科学基金;国家高技术研究发展计划(863计划)
论文部分内容阅读
Indirect association is a high level relationship between items and frequent itemsets in data. Current research approaches on indirect association mining are limited to indirect association between itempairs, which will discovertoo many rules from dataset. A formal definition of indirect association between multiple items is presented, along with an algorithm, SET-NIA,for mining this kind of indirect associations based on anti-monotonicity of indirect associations and frequent itempair support matrix. While the found rules contain same information as compared to the rules found by indirect association between itempairs mining algorithms, this notion brings space-saving in storage ofthe rules as well as superiority for human to understand and apply the rules. Experiments conducted on two real-word datasets show that SET-NIA can effectively find fewer rules than existing algorithms which mine indirect association between itempairs, the experimental results also prove that SET-NIA has better performance than existing algorithms.
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