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https://ieeexplore.ieee.org/document/1316834/
Abstract: In classical association rules mining, a minimum support threshold is assumed to be available for mining frequent itemsets. However, setting such a threshold is typically hard. However, setting such a threshold is typically hard.Cited by: 175
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.75.3523
Abstract—In classical association rules mining, a minimum support threshold is assumed to be available for mining frequent itemsets. However, setting such a threshold is typically hard. In this paper, we handle a more practical problem; roughly speaking, it is to mine N k-itemsets with the highest supports for k up to a certain kmax value.
https://www.researchgate.net/publication/3297302_Mining_Frequent_Itemsets_without_Support_Threshold_With_and_Without_Item_Constraints
In classical association rules mining, a minimum support threshold is assumed to be available for mining frequent itemsets. However, setting such a threshold is typically hard.
http://www.cse.cuhk.edu.hk/~adafu/Pub/IJBIDM05.pdf
frequent itemsets. All the above proposed algorithms focus on the problem of mining frequent itemsets with frequency greater than a support threshold. However, it is difficult for the users to determine the threshold value. If the threshold is set too large, then there are no frequent itemsets …
http://gkmc.utah.edu/7910F/papers/IEEE%20TKDE%20mining%20frequent%20itemsets.pdf
Mining Frequent Itemsets without Support Threshold: With and without Item Constraints Yin-Ling Cheung and Ada Wai-Chee Fu,Member, IEEE Abstract—In classical association rules mining, a minimum support threshold is assumed to be available for mining frequent itemsets. However, setting such a threshold is typically hard.
https://link.springer.com/chapter/10.1007%2F978-3-319-06538-0_13
Therefore, in this paper, we propose an alternative approach to mine the most interesting multi-level frequent patterns without the setting of support threshold, called N-most interesting multi-level frequent pattern mining, where N is the number of desired patterns with the highest support values per each category level.Author: Sorapol Chompaisal, Komate Amphawan, Athasit Surarerks
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