文献类型：期刊文章

作　　者：范明[1] 王秉政[1]

机构地区：[1]郑州大学计算机科学系,郑州450052

出　　处：《计算机科学》

基　　金：河南省自然科学基金(项目号:0111060700;0211050100)

年　　份：2003

卷　　号：30

期　　号：8

起止页码：117-120

语　　种：中文

收录情况：BDHX、BDHX2000、CSA、CSCD、CSCD2011_2012、IC、JST、RCCSE、UPD、ZGKJHX、核心刊

摘　　要：Frequent pattern mining plays an essential role in many important data mining tasks. FP-growth is a veryefficient algorithm for frequent pattern mining. However, it still suffers from creating conditional FP-tree separatelyand recursively during the mining process. In this paper, we propose a new algorithm, called Least-Item-First Pat-tern Growth (LIFPG), for mining frequent patterns. LIFPG mines frequent patterns directly in Trans-tree withoutusing any additional data structures. The key idea is that least items are always considered first when the current pat-tern growth. By this way, conditional sub-tree can be created directly in Trans-tree by adjusting node-links and re-counting counts of some nodes. Experiments show that, in comparison with FP-Growth, our algorithm is about fourtimes faster and saves half of memory; it also has good time and space scalability with the number of transactions,and has an excellent performance in dense dataset mining as well.

关 键 词：频繁模式  关联规则 数据库 Trans-树  数据挖掘 算法  

分 类 号：TP311.13]