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International Conference on Scientific and Statistical Database Management

SSDBM 2011: Scientific and Statistical Database Management pp 596–597Cite as

An Adaptive Outlier Detection Technique for Data Streams

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6809))

Abstract

This work presents an adaptive outlier detection technique for data streams, called Automatic Outlier Detection for Data Streams (A-ODDS), which identifies outliers with respect to all the received data points (global context) as well as temporally close data points (local context) where local context are selected based on time and change of data distribution.

This work has been supported in part by the NASA under the grants No. NNG05GA30G.

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References

  1. Barnett, V., Lewis, T.: Outliers in Statistical Data. Wiley Series in Probability and Mathematical Statistics. John Wiley & Sons Inc., Chichester (1994)

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  5. Sadik, S., Gruenwald, L.: DBOD-DS: Distance Based Outlier Detection for Data Streams. In: Bringas, P.G., Hameurlain, A., Quirchmayr, G. (eds.) DEXA 2010. LNCS, vol. 6261, pp. 122–136. Springer, Heidelberg (2010)

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Author information

Authors and Affiliations

  1. School of Computer Science, University of Oklahoma, Norman, OK, 73071, USA

    Shiblee Sadik & Le Gruenwald

Authors
  1. Shiblee Sadik
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  2. Le Gruenwald
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Editor information

Editors and Affiliations

  1. The Evergreen State College, 98505, Olympia, WA, USA

    Judith Bayard Cushing

  2. CNRI and University of Virginia, 22908, Charlottesville, VA, USA

    James French

  3. Gonzaga University, 99258, Spokane, WA, USA

    Shawn Bowers

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© 2011 Springer-Verlag Berlin Heidelberg

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Cite this paper

Sadik, S., Gruenwald, L. (2011). An Adaptive Outlier Detection Technique for Data Streams. In: Bayard Cushing, J., French, J., Bowers, S. (eds) Scientific and Statistical Database Management. SSDBM 2011. Lecture Notes in Computer Science, vol 6809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22351-8_52

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  • DOI: https://doi.org/10.1007/978-3-642-22351-8_52

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22350-1

  • Online ISBN: 978-3-642-22351-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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