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Effective Similarity Analysis over Event Streams Based on Sharing Extent

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Part of the book series:Lecture Notes in Computer Science ((LNISA,volume 5446))

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Abstract

With the development of event-driven applications, event stream processing has received more and more attentions in database community. However, little work has focused on the problem of data mining and similarity analysis among event streams. As the foundation for the data mining such as frequent or abnormal event pattern detection, efficient similarity search is desired to be first executed. In this paper, we attempt to take the first step into the similarity search in the context of vast event streams. We propose a simple but effective model to improve the efficiency of the similarity search. To avoid redundant pair-wise comparison, we adopt the definition of sharing extent to dramatically filter dissimilar event streams and speed up the calculation of similarity. Extensive simulated experiments have demonstrated that our model and algorithm can lead to higher efficiency when guaranteeing expected accuracy.

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Author information

Authors and Affiliations

  1. School of Information Science and Engineering, Northeastern University, China

    Yanqiu Wang, Ge Yu, Tiancheng Zhang, Dejun Yue, Yu Gu & Xiaolong Hu

Authors
  1. Yanqiu Wang

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  2. Ge Yu

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  3. Tiancheng Zhang

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  4. Dejun Yue

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  5. Yu Gu

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  6. Xiaolong Hu

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Editor information

Editors and Affiliations

  1. Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, China

    Qing Li

  2. Department of Computer Science & Technology, Tsinghua University, Beijing, China

    Ling Feng

  3. School of Computing Science, Simon Fraser University, 8888 University Drive, V5A 1S6, Burnaby BC, Canada

    Jian Pei

  4. Department of Computer Science, University of Vermont, VT 05405, Burlington, USA

    Sean X. Wang

  5. School of Information Technology and Electrical Engineering, The University of Queensland, QLD 4072, Brisbane, Australia

    Xiaofang Zhou

  6. Jiangsu Provincial Key Lab of Computer Information Processing Technology School of Computer Science & Technology, Soochow University China, 1 shizi Street Suzhou, 215006, Jiangsu, China

    Qiao-Ming Zhu

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© 2009 Springer-Verlag Berlin Heidelberg

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Wang, Y., Yu, G., Zhang, T., Yue, D., Gu, Y., Hu, X. (2009). Effective Similarity Analysis over Event Streams Based on Sharing Extent. In: Li, Q., Feng, L., Pei, J., Wang, S.X., Zhou, X., Zhu, QM. (eds) Advances in Data and Web Management. APWeb WAIM 2009 2009. Lecture Notes in Computer Science, vol 5446. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00672-2_28

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