Fast Algorithm for Finding the Value-Added Utility Frequent Itemsets Using Apriori Algorithm

Provided by: International Journal of Computing Science and Information Technology (IJCSIT)
Topic: Big Data
Format: PDF
In association rule mining, frequency of an itemset alone does not assure its interestingness because it does not contain information on subjectively defined utility such as profit in rupees or some other variety of utility. This leads to a fruitful deviation in the frequent itemset mining called utility based data mining. Mining high utility itemsets upgrades the standard frequent itemset mining framework. Fast Utility Frequent Mining (FUFM) is a popular algorithm to find Utility Frequent ItemSets (UFIS) based on the extended support measure. But, when applying FUFM on transactional databases with highly fluctuated transaction utility values, it generates less number of UFIS.

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