关联挖掘研究综述  

Review on Association Mining

作　　者：王卉[1] 张红君[2] 

机构地区：[1]中国人民解放军武汉通信指挥学院,湖北武汉430010 [2]中国人民解放军161医院,湖北武汉430010

出　　处：《软件导刊》2009年第3期7-8,共2页Software Guide

基　　金：国家自然科学基金项目(60603069)

摘　　要：数据挖掘是一种重要的数据分析方法,旨在发现庞大的数据中隐藏着的、先前未知的并潜在有用的模式和信息,以帮助人们正确理解和认识数据,进行科学决策。关联挖掘是数据挖掘中研究最早也是最活跃的领域,其中,频繁模式挖掘是关联挖掘的核心和基础。对关联挖掘算法的研究和发展进行综述,分析挖掘算法面临的主要挑战,概括最新研究进展。data mining is a very important data analysis method for people to understand data to make correct decision by discovering unknown and useful information and patterns hidden in data.Association mining is the most classical and active field of mining where frequent pattern mining is its core and base.A lot of achievements are improving the performance of mining algorithms.The applications of the representative mining methods are reviewed.The challenges they currentIy face and the corresponding strategies have been analyzed. Some noticeable work for further improving the performance including parallelization and pruning are discussed.

关 键 词：数据挖掘 关联挖掘 剪枝 并行算法 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]