西南交通大学学报(英文版)2002，Vol.10Issue(1)：10-20,11.
A New Algorithm for Mining Frequent Pattern
A New Algorithm for Mining Frequent Pattern
摘要
Abstract
Mining frequent pattern in transaction database, time-series databases, and many other kinds of databases have been studied popularly in data mining research. Most of the previous studies adopt Apriori-like candidate set generation-and-test approach. However, candidate set generation is very costly. Han J. proposed a novel algorithm FP-growth that could generate frequent pattern without candidate set. Based on the analysis of the algorithm FP-growth, this paper proposes a concept of equivalent FP-tree and proposes an improved algorithm, denoted as FP-growth*, which is much faster in speed, and easy to realize. FP-growth* adopts a modified structure of FP-tree and header table, and only generates a header table in each recursive operation and projects the tree to the original FP-tree. The two algorithms get the same frequent pattern set in the same transaction database, but the performance study on computer shows that the speed of the improved algorithm, FP-growth*, is at least two times as fast as that of FP-growth.关键词
data mining/algorithm/frequent pattern set/FP-growthKey words
data mining/algorithm/frequent pattern set/FP-growth分类
信息技术与安全科学引用本文复制引用
李力,靳蕃..A New Algorithm for Mining Frequent Pattern[J].西南交通大学学报(英文版),2002,10(1):10-20,11.基金项目
Supported by the Fund of the National Management Bureau of Traditional Chinese Medicine (No.2000-J-P-54). （No.2000-J-P-54）
