文章基本信息

标题：Distributed Count Association Rule Mining Algorithm
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作者：Tirumala prasad B ; Dr. MHM Krishna Prasad
期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2011
卷号：1
期号：3-2
出版社：Seventh Sense Research Group
摘要：—With the explosive growth of information sources available on the World Wide Web, it has become increasingly necessary for users to utilize automated tools to find the desired information resources, and to track and analyze their usage patterns. Association rule mining is an active data mining research area. However, most ARM algorithms cater to a centralized environment. In contrast to previous ARM algorithms, Optimized Distributed Association Rule Mining (ODARM) is a distributed algorithm for geographically spread data sets that aimed to reduces operational/ communication costs. Recently, as the need to mine patterns across distributed databases has grown, Distributed Association Rule MiningIn the special case of databases populated from information extracted from textual data, existing DARM algorithms cannot discover rules based on higherorder associations between items in distributed textual documents that are neither vertically nor horizontally distributed, but rather a hybrid of the two. Hence, this paper proposes a Distributed Count Association Rule Mining Algorithm(DCARM), which is experimented on real time datasets obtained from UCI machine learning repository.
关键词：ARM algorithm; ODARM; DARM; PARM