Mining Weighted Association Rules with Lucene Index

摘要：

Discovery of association rules has been found useful in many applications. With large database, the process of mining association rules is time consuming. The efficiency becomes crucial factor. Weighted association is more meaningful in some application. This paper implements a fast and stable algorithm to mining weighted association rules base on the open source library Lucene. The methods to create index in Lucene and utilization of the index to find weighted frequent itemsets are introduced. Based on Apriori algorithm, a weighted association rule mining algorithm is implemented. All the rules can be recommended to customer by searching Lucene Index. Experiment shows that this method is more efficient than general Apriori algorithm.

关键词： data mining association rules Lucene index frequent itemsets.

作者: Ning zhou JiaXin Wu ShaoLong Zhang HongQin Chen XiangRong Zhang

作者单位: Research Center of Information Resources, School of information Management, Wuhan University, Wuhan 430072 China

会议类型: 国际会议

会议名称: 第三届IEEE无线通讯、网络技术暨移动计算国际会议

会议地点: 上海

会议语种:英文

在线出版日期: 2007-09-21（万方平台首次上网日期，不代表论文的发表时间）