期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2014
卷号：2
期号：10
出版社：S&S Publications
摘要：Data Mining is the process of analyzing data from different perspectives and summarizing it into usefulinformation. An association in data mining indicates a logical dependency between various attributes of an entity.Association rule mining (ARM) is the process of mining past data for association rules. ARM only find the frequencyof itemsets, which will not provide large amount of profit. Utility mining focuses on discovering the itemsets with highsales profit. Here, utility mining is a measure of profitability of items to the users. The utility mining of itemsets is animportant task in decision-making process of many applications such as website click streaming analysis, crossmarketing in retail stores and in biomedical applications. The extraction of the high utility itemsets from a largedatabase involves the creation of new candidate itemsets with high utility. This affects the performance of the miningprocess in terms of the execution time and the space requirement.In this paper, it is intended to develop an efficient algorithm for mining the high utility itemsets for reducingthe candidate itemsets. Here, a data structure named pattern tree would be maintained to store the information about thehigh utility itemsets, so that the number of database scans can be reduced.
