A regression-based Temporal Pattern mining scheme for Data Streams

Wei Guang Teng, Ming Syan Chen, Philip S. Yu

研究成果: Conference contribution

96 引文 斯高帕斯(Scopus)

摘要

We devise in this paper a regression-based algorithm, called algorithm FTP-DS (Frequent Temporal Patterns of Data Streams), to mine frequent temporal patterns for data streams. While providing a general framework of pattern frequency counting, algorithm FTP-DS has two major features, namely one data scan for online statistics collection and regressionbased compact pattern representation. To attain the feature of one data scan, the data segmentation and the pattern growth scenarios are explored for the frequency counting purpose. Algorithm FTP-DS scans online transaction flows and generates candidate frequent patterns in real time. The second important feature of algorithm FTP-DS is on the regression-based compact pattern representation. Specifically, to meet the space constraint, we devise for pattern representation a compact ATF (standing for Accumulated Time and Frequency) form to aggregately comprise all the information required for regression analysis. In addition, we develop the techniques of the segmentation tuning and segment relaxation to enhance the functions of FTP-DS. With these features, algorithm FTP-DS is able to not only conduct mining with variable time intervals but also perform trend detection effectively. Synthetic data and a real dataset which contains network alarm logs from a major telecommunication company are utilized to verify the feasibility of algorithm FTP-DS.

原文English
主出版物標題Proceedings - 29th International Conference on Very Large Data Bases, VLDB 2003
編輯Patricia G. Selinger, Michael J. Carey, Johann Christoph Freytag, Serge Abiteboul, Peter C. Lockemann, Andreas Heuer
發行者Morgan Kaufmann
頁面93-104
頁數12
ISBN(電子)0127224424, 9780127224428
出版狀態Published - 2003 一月 1
事件29th International Conference on Very Large Data Bases, VLDB 2003 - Berlin, Germany
持續時間: 2003 九月 92003 九月 12

出版系列

名字Proceedings - 29th International Conference on Very Large Data Bases, VLDB 2003

Other

Other29th International Conference on Very Large Data Bases, VLDB 2003
國家Germany
城市Berlin
期間03-09-0903-09-12

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems
  • Hardware and Architecture
  • Information Systems and Management
  • Computer Science Applications
  • Computer Networks and Communications

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  • 引用此

    Teng, W. G., Chen, M. S., & Yu, P. S. (2003). A regression-based Temporal Pattern mining scheme for Data Streams. 於 P. G. Selinger, M. J. Carey, J. C. Freytag, S. Abiteboul, P. C. Lockemann, & A. Heuer (編輯), Proceedings - 29th International Conference on Very Large Data Bases, VLDB 2003 (頁 93-104). (Proceedings - 29th International Conference on Very Large Data Bases, VLDB 2003). Morgan Kaufmann.