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挖掘多数据流的异步偶合模式的抗噪声算法
引用本文:陈安龙,唐常杰,元昌安,彭京,胡建军.挖掘多数据流的异步偶合模式的抗噪声算法[J].软件学报,2006,17(8):1753-1763.
作者姓名:陈安龙  唐常杰  元昌安  彭京  胡建军
作者单位:1. 四川大学,计算机学院,四川,成都,610065;电子科技大学,计算机科学与工程学院,四川,成都,610054
2. 四川大学,计算机学院,四川,成都,610065
3. 四川大学,计算机学院,四川,成都,610065;广西师范学院,信息技术系,广西,南宁,530001
基金项目:中国科学院资助项目;高等学校博士学科点专项科研项目
摘    要:挖掘多数据流的异步偶合模式是具有挑战性的工作.主要的研究工作包括:(1) 研究Haar小波滤波技术在挖掘流数据的异步偶合模式中的应用;(2) 引入小波系数序列来度量数据流的异步局域偶合度;证明了一系列定理,保证了度量方法的正确性;(3) 设计了环形滑动窗口和挖掘异步偶合模式的抗噪声增量算法,其时间复杂性小于O(n2);(4) 使用真实数据进行模拟实验,验证了算法的有效性.

关 键 词:多数据流  异步偶合模式  Haar小波  环形滑动窗口
收稿时间:2005-07-28
修稿时间:2005-12-01

An Anti-Noise Algorithm for Mining Asynchronous Coincidence Pattern in Multi-Streams
CHEN An-Long,TANG Chang-Jie,YUAN Chang-An,PENG Jing and HU Jian-Jun.An Anti-Noise Algorithm for Mining Asynchronous Coincidence Pattern in Multi-Streams[J].Journal of Software,2006,17(8):1753-1763.
Authors:CHEN An-Long  TANG Chang-Jie  YUAN Chang-An  PENG Jing and HU Jian-Jun
Affiliation:1.College of Computer, Sichuan University, Chengdu 610065, China; 2.College of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China; 3.Department of Information Technology, Guangxi Teachers Education University, Nanning 530001, China
Abstract:Mining asynchronous coincidence pattern is a difficult task in multi-data streams. The main contributions of this work included: (1) The filter technique of Haar Wavelet is investigated and applied to mining asynchronous coincidence pattern in multi-streams; (2) The Wavelet coefficient series are applied to the measurement of asynchronous coincidence between data streams. A series of theorems are proved to ensure the validity of measuring asynchronous coincidence; (3) The anti-noise increment algorithms are designed on loop sliding windows to mine asynchronous coincidence pattern and implemented with complexity O(n2); (4) The extensive experiments on real data are given to validate algorithms.
Keywords:multi-data stream  asynchronous coincidence pattern  Haar wavelet  loop sliding window
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