A Study on Top-K High Utility Itemsets Mining

Ameena Aiman, Raafiya Gulmeher

Abstract


High utility itemsets (HUIs) mining is an emerging topic in data mining, which refers to discovering all itemsets having a utility meeting a user-specified minimum utility threshold min_util. However, setting min_util appropriately is a difficult problem for users. Finding an appropriate minimum utility threshold by trial and error is a tedious process for users. If min_util is set too low, too many HUIs will be generated, which may cause the mining process to be very inefficient. On the other hand, if min_util is set too high, it is likely that no HUIs will be found. In this paper, we study top-k high utility itemset mining, where k is the desired number of HUIs to be mined.


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