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An adaptive algorithm for finding frequent sets in landmark windows

Dang, Xuan Hong, Ong, Kok-Leong and Lee, Vincent 2012, An adaptive algorithm for finding frequent sets in landmark windows. In Hüllermeier, Eyke, Link, Sebastian, Fober, Thomas and Seeger, Bernhard (ed), Scalable uncertainty management, Springer Berlin Heidelberg, Berlin, Germany, pp.590-597.

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Title An adaptive algorithm for finding frequent sets in landmark windows
Author(s) Dang, Xuan Hong
Ong, Kok-Leong
Lee, Vincent
Title of book Scalable uncertainty management
Editor(s) Hüllermeier, Eyke
Link, Sebastian
Fober, Thomas
Seeger, Bernhard
Publication date 2012
Series Lecture notes in artificial intelligence; vol. 7520
Chapter number 47
Total chapters 54
Start page 590
End page 597
Total pages 8
Publisher Springer Berlin Heidelberg
Place of Publication Berlin, Germany
Summary We consider a CPU constrained environment for finding approximation of frequent sets in data streams using the landmark window. Our algorithm can detect overload situations, i.e., breaching the CPU capacity, and sheds data in the stream to “keep up”. This is done within a controlled error threshold by exploiting the Chernoff-bound. Empirical evaluation of the algorithm confirms the feasibility.
Notes 6th International Conference, SUM 2012 Marburg, Germany, September 17-19, 2012 Proceedings
ISBN 3642333613
ISSN 0302-9743
Language eng
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 890205 Information Processing Services (incl. Data Entry and Capture)
HERDC Research category B1 Book chapter
Copyright notice ©2012, Springer
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Document type: Book Chapter
Collection: School of Information Technology
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Created: Thu, 29 Nov 2012, 07:55:50 EST

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