An Algorithm Research for Distributed Association Rules Mining with Constraints Based on Sampling

摘要：

An algorithm for distributed mining association rules -with constraints called DMCASE is presented using Sampling and constraint-based Eclat algorithm. At each database site, Sampling algorithm and constraint-based Eclat algorithm are implemented. And the local frequent itemsets satisfying constraints are developed. They then are combined to global frequent itemsets satisfying constraints based on inductive learning method. DMCASE algorithm scans the whole database only once. It is also an algorithm with high efficiency. Results from our experiments show that the algorithm is an effective way to resolve the problem of distributed mining association rules with constraints.

关键词： Data Mining Association Rules with Constraints Sampling.

作者: Hong Li Song-qiao Chen Jian-feng Du Li-jun Yi Wei Xiao

作者单位: School of Information Science and Engineering, Central South University, Changsha 410083, P.R China

会议类型: 国际会议

会议名称: Firth IEEE International Conference on Cognitive Informatics(第五届认知信息国际会议)

会议地点: 北京

会议语种:英文

页码: 478-483

在线出版日期: 2006-07-17（万方平台首次上网日期，不代表论文的发表时间）