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：2015
卷号：3
期号：11
DOI：10.15680/IJIRCCE.2015.0311059
出版社：S&S Publications
摘要：Utility mining is the application of data mining techniques to discover patterns from the datasets.Itemset extraction and utility mining is characterized by a frequency analysis where the item values correspond to thenumber of times that term appears in the database. Fast Apriori indexing based hierarchical clustering gives a usefulmeasure which is used to measure the item dependency between data points that is likely to be in terms of theirminimum support property. This research proposes an optimal method to estimate the items searching which ismeasured using indexing method corresponds to transactional database. Each item contains number of transactionfunctions and its own description which is used to identify the type of database. Further, the proposed methodology offinding the relevant item sets can maintain better quality in terms of relevance utility discovery than the existingmethods. Our approach can reduce the number of support count dependencies to be checked in comparison withprevious methods.
关键词：Utility Mining; Frequent Itemsets; Fast Apriori; High utility Itemset; Downward Closure Property;(DCP).
