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A Hybrid Method for Detecting Data Stream Changes with Complex Semantics in Intensive Care Unit

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Advances in Computer Science – ASIAN 2005. Data Management on the Web (ASIAN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3818))

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Abstract

Detecting changes in data streams is very important for many applications. This paper presents a hybrid method for detecting data stream changes in intensive care unit. In the method, we first use query processing to detect all the potential changes supporting semantics in big granularity, and then perform similarity matching, which has some features such as normalized subsequences and weighted distance. Our approach makes change detection with a better trade-off between sensitivity and specificity. Experiments on ICU data streams demonstrate its effectiveness.

Supported by Natural Science Foundation of China (NSFC) under grant number 60473072.

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References

  1. Zhu, Y., Shasha, D.: StatStream: Statistical Monitoring of Thousands of Data Streams in Real Time. In: VLDB, pp. 358–369 (2002)

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Author information

Authors and Affiliations

  1. School of Electronics Engineering and Computer Science, Peking University, Beijing, 100871, P.R. China

    Ting Yin, Hongyan Li, Zijing Hu, Yu Fan, Jianlong Gao & Shiwei Tang

Authors
  1. Ting Yin
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  2. Hongyan Li
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  3. Zijing Hu
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  4. Yu Fan
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  5. Jianlong Gao
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  6. Shiwei Tang
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Editor information

Editors and Affiliations

  1. INRIA-LIAMA Institute of Automation, Beijing, China

    Stéphane Grumbach

  2. Computer Science and Engineering Department, San Diego, University of California, 92093-0404, La Jolla, CA, USA

    Liying Sui

  3. UC San Diego, USA

    Victor Vianu

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© 2005 Springer-Verlag Berlin Heidelberg

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Yin, T., Li, H., Hu, Z., Fan, Y., Gao, J., Tang, S. (2005). A Hybrid Method for Detecting Data Stream Changes with Complex Semantics in Intensive Care Unit. In: Grumbach, S., Sui, L., Vianu, V. (eds) Advances in Computer Science – ASIAN 2005. Data Management on the Web. ASIAN 2005. Lecture Notes in Computer Science, vol 3818. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596370_39

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  • DOI: https://doi.org/10.1007/11596370_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30767-9

  • Online ISBN: 978-3-540-32249-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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