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Detecting abnormal trend evolution over multiple data streams

  • Chen Zhang*
  • , Nianlong Weng
  • , Jianlong Chang
  • , Aoying Zhou
  • *此作品的通讯作者
  • Fudan University
  • Shanghai Stock Exchange
  • ShangHai Telecom Company
  • Shanghai Key Laboratory of Trustworthy Computering

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

In this paper, we present a method to trace evolution of trend over multiple data streams and detect the abnormal ones. First of all, a definition of trend for single data stream is provided, the advantage of our definition lies in its low time and space cost. Second, we improve a SVD-based method in order to select a pair of optimal initial parameters, then a novel chessboard named sketch is also illustrated aim at adjusting the parameters dynamically. Then, utilizing the skewness of trend distribution, an anomaly detection strategy is briefly introduced. Finally, we implement experiment on a variety of real data sets to illustrate effectiveness and efficiency of our approach.

源语言英语
主期刊名Advances in Data and Web Management - Joint International Conferences, APWeb/WAIM 2009, Proceedings
出版商Springer Verlag
285-296
页数12
ISBN(印刷版)9783642006715
DOI
出版状态已出版 - 2009
活动Joint International Conference on Advances in Data and Web Management, APWeb/WAIM 2009 - Suzhou, 中国
期限: 2 4月 20094 4月 2009

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
5446
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议Joint International Conference on Advances in Data and Web Management, APWeb/WAIM 2009
国家/地区中国
Suzhou
时期2/04/094/04/09

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