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：2017
卷号：5
期号：1
页码：56
DOI：10.15680/IJIRCCE.2017.0501007
出版社：S&S Publications
摘要：Data mining is gaining importance due to huge amount of data available. Retrieving information fromthe warehouse is not only tedious but also difficult in some cases. The existing algorithm does not provide fastcomputation and better result. Frequent itemset using density based spatial clustering is used in the proposed system sothat support is counted by mapping the items from the candidate list into the buckets which is divided according tosupport known as Hash table structure. As the new itemset is encountered if item exist earlier then increase the bucketcount else insert into new bucket. Thus in the end the bucket whose support count is less the minimum support isremoved from the candidate set.
