期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2016
卷号：7
期号：2
页码：858-863
出版社：TechScience Publications
摘要：Discovering interesting patterns like popularcrime patterns from various geographical locations plays animportant role in data mining and knowledge discoveryprocess. The researchers have been extended the frequentpatterns to different useful patterns such as sequential, cyclic,emerging, periodic and many other interesting patterns.PPCrime-growth algorithm has been introduced and itinvolves in mining popular crime patterns from variousgeographical locations. In performing, it captures thepopularity of individual crimes among their peers or groupsor crimes at their local site. PPCrime-tree will be constructedat every local node in the first phase which captures theessential data for the global mining process. In the next phasepopular crime patterns will be extracted from PPCrime-treein parallel. PPCrime-algorithm will work in parallel at eachlocal site in order to reduce I/O cost and also Inter-processcommunication between nodes. Our method generates allpopular crime patterns in the final phase. The experimentresults show that our PPCrime-method is highly efficient inmultidimensional databases.
