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：8
DOI：10.15680/IJIRCCE.2015. 0308042
出版社：S&S Publications
摘要：Mining high utility itemsets from databases is an important data mining task for discovery of itemsetswith high utilities. However, it may present too many HUIs to users, which also degrades the efficiency of the miningprocess. Frequent itemset mining (FIM) is a one of its popular applications is market basket analysis, which refers tothe discovery of sets of items (itemsets) that are frequently purchased together by customers. In this paper presents anew system to utilize the model for building a Lossless Representation system that suggests high utility itemsets overdynamic datasets using the Fast Apriori closed high utility itemset discovery with hierarchical clustering algorithm(FAHU-Hierarchical). Update the CHUD (Closed High Utility Itemset Discovery) to approach divisive Hierarchicalclustering manner. The proposed FAHU-Hierarchical clustering method attempts to address the individual requirementsin utility clustering using the notion of frequent itemsets. Its works greedily selects the next frequent itemset, whichrepresents the next cluster, minimizing the overlap of clusters in terms of shared documents. Experimental studies onboth the synthetic and real-world data streams show the performance of our proposed approach.
关键词：High utility mining; Fast Apriori algorithm; Hierarchical clustering; frequent mining
