Research overview of related techniques and algorithms on frequent pattern mining in data stream

doi:10.3778/j.issn.1002-8331.2009.26.036

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (26): 121-125.DOI: 10.3778/j.issn.1002-8331.2009.26.036

• 数据库、信息处理 • Previous Articles Next Articles

Research overview of related techniques and algorithms on frequent pattern mining in data stream

TANG Yi-fang^1,2，MU Zhi-chun¹，ZHANG Shi-chao^3,4，ZHONG Da-fu²

1.School of Information Engineering，University of Science and Technology Beijing，Beijing 100083，China
2.Computer Engineering Technical College，Guangdong Institute of Science and Technology，Zhuhai，Guangdong 519090，China
3.College of Computer Science and Information Technology，Guangxi Normal University，Guilin，Guangxi 541004，China
4.Faculty of Information Technology，Sudney University of Technology，Sydney，Australia

Received:2008-05-16 Revised:2008-08-04 Online:2009-09-11 Published:2009-09-11
Contact: TANG Yi-fang

挖掘数据流频繁模式的相关技术和算法研究综述

唐懿芳^1,2，穆志纯¹，张师超^3,4，钟达夫²

1.北京科技大学信息工程学院，北京 100083
2.广东科技干部管理学院计算机工程技术学院，广东珠海 519090
3.广西师范大学计算机科学与信息工程学院，广西桂林 541004
4.悉尼理工大学信息技术学院，澳大利亚悉尼

通讯作者: 唐懿芳

Abstract

Abstract: Some characters of Data stream make that static mining method can’t meet the requirements of nowadays mining application.Many new techniques and methods on frequent pattern mining in data stream have been proposed.In this paper，we give an overview of these algorithms.Firstly，the concept and characters of data stream are introduced.Then related research work about data streams are introduced at home and abroad.The characters of mining frequent pattern in data stream are analyzed，and the common techniques and the representative algorithms of mining are listed.At last，future directions in data stream mining research are discussed.

Key words: data stream, frequent pattern, synopsis data structure, decay factor, tilted time window

摘要： 数据流本身的特点使得静态挖掘方法不再满足要求。国内外学者已提出许多新的挖掘数据流频繁模式的方法和技术。对这些技术和算法进行了综述。首先介绍数据流的概念和特点，分析国内外的研究现状，总结了数据流中挖掘频繁模式的特点，并列出挖掘方法的常用技术和基于这些技术的代表性算法，最后讨论了将来的研究方向。

关键词: 数据流, 频繁模式, 概要数据结构, 衰减因子, 倾斜时间窗口

CLC Number:

TP311

TANG Yi-fang^1,2，MU Zhi-chun¹，ZHANG Shi-chao^3,4，ZHONG Da-fu². Research overview of related techniques and algorithms on frequent pattern mining in data stream[J]. Computer Engineering and Applications, 2009, 45(26): 121-125.

唐懿芳^1,2，穆志纯¹，张师超^3,4，钟达夫². 挖掘数据流频繁模式的相关技术和算法研究综述[J]. 计算机工程与应用, 2009, 45(26): 121-125.

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Research overview of related techniques and algorithms on frequent pattern mining in data stream

挖掘数据流频繁模式的相关技术和算法研究综述

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