A Hybrid Method for Detecting Data Stream Changes with Complex Semantics in Intensive Care Unit | SpringerLink
Skip to main content
Springer Nature Link
Log in

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

  • Conference paper
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))

Included in the following conference series:

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
JPY 3498
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
JPY 5719
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
JPY 7149
Price includes VAT (Japan)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

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

    Google Scholar 

  2. Goldin, D.Q., Millstein, T.D., Kutlu, A.: Bounded similarity query for time series data. Information and Computation 194, 203–241 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  3. Wu, H., Salzberg, B., Zhang, D.: Online Event-driven Subsequence Matching over Financial Data Streams. In: SIGMOD 2004, Paris, France (2004)

    Google Scholar 

Download references

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
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hongyan Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zijing Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yu Fan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jianlong Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Shiwei Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

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

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

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

Download citation

  • 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)

Publish with us

Policies and ethics

Search

Navigation