IULFP: An Efficient incremental updating Algorithm based on LFP-tree for Mining Association Rules

摘要：

Dynamic rules acquisition is a topic of general interest in the field of association rules mining. Many existing incremental mining algorithms are Apriori-based, which are not easily adoptable to mine tree-based frequent patterns. In this paper, we provide a novel incremental updating algorithm IULFP for mining association rules. We use the layered frequent pattern tree based structure to store frequent items. Moreover, we propose the definition of strong frequent itemsets, which is proved to be a useful method to find all the frequent itemsets in the updated databases. The experimental results show that our approach has higher efficiency than other previous works.

关键词： association rules mining incremental updating layered frequent pattern tree strong frequent itemsets

作者: Tongyan Li Xingming Li

作者单位: Key Laboratory of Broadband Optical Fiber Transmission and Communication Networks of Ministry of Edu Key Laboratory of Broadband Optical Fiber Transmission and Communication Networks of Ministry of Edu

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 426-430

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）