A Novel Approach to Identifying Global Exceptional Patterns in Distributed Data Mining
With the increasing development and application of distributed database,distributed data mining has attracted many data mining researchers attention.In this paper,a framework for distributed data mining is introduced,and based on the framework,many patterns are generated from each database after data mining,so it is necessary to synthesize all the patterns to identify the meaningful global patterns.An approach to synthesizing local patterns to identifying global exceptional patterns is developed.In this approach,a patterns significance is measured by the deviation of the patterns support from the average support.Experimental results show that our approach is reasonable and appropriate to identify exceptional patterns.
distributed data mining local pattern global pattern global exceptional pattern
Meiling Liu
College of Mathematics and Computer Science,Guangxi University for Nationalities Nanning,China
国际会议
沈阳
英文
1972-1977
2012-09-07（万方平台首次上网日期，不代表论文的发表时间）