Email this article High Utility Itemsets Mining for Transactional Databases
Abstract
Mainstream issue in data mining, which is called "high-utility itemset mining" or all the more for the most part utility mining. High Utility Itemsets which are itemsets having an utility gathering a client determined least utility edge value i.e min_util. The principle target of utility mining is to discover thing sets with highest utilities, by thinking about benefit, amount, cost or some other client inclinations. Research has been done in region of mining HUI's. Different procedures have been connected. The fundamental issue with setting edge value which is for the most part client particular, is it should be proper. In Order to set most fitting or right Threshold value for mining HUI's,user needs to do trial and mistake which thus is tedious and repetitive process, in light of the fact that if min_util is set too low, framework will bring about getting substantial data of HUI, which thus makes framework incapable with the end goal of HUI. In the event that we set min_util too high, this will bring about getting little sum or no HUI's. Consequently setting least edge value is troublesome. The proposed framework is following Top-k framework for mining top-k HUI's, which is utilizing two algorithms TKU (mining top-k utility itemsets) and TKO (mining top-k in one phase),without setting min_util edge.
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