Full Citation

Title: Mining N-most Interesting Itemsets

Citation Type: Miscellaneous

Publication Year: 2000

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Abstract: Previous methods on mining association rules require usersto input a minimum support threshold. However, there can be too manyor too few resulting rules if the threshold is set inappropriately. It isdi$cult for end-users to nd the suitable threshold. In this paper, wepropose a di erent setting in which the user does not provide a supportthreshold, but instead indicates the amount of results that is required.

User Submitted?: No

Authors: Wai-chee Fu, Ada; Tang, Jian; Wange-wai Kwong, Renfrew

Publisher: The Chinese University of Hong Kong

Data Collections: IPUMS USA

Topics: Other

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