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Subsequence frequency measurement and its impact on knowledge discovery in single sequences

Gan, Min and Dai, Honghua 2012, Subsequence frequency measurement and its impact on knowledge discovery in single sequences, in Reliable knowledge discovery, Springer, New York, N. Y., pp.239-255.

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Title Subsequence frequency measurement and its impact on knowledge discovery in single sequences
Author(s) Gan, Min
Dai, Honghua
Title of book Reliable knowledge discovery
Editor(s) Dai, Honghua
Liu, James N. K.
Smirnov, Evgueni
Publication date 2012
Chapter number 14
Total chapters 17
Start page 239
End page 255
Total pages 17
Publisher Springer
Place of Publication New York, N. Y.
Keyword(s) subsequence frequency measurement
frequency metrics
frequency based knowledge discovery
Summary Subsequence frequency measurement is a basic and essential problem in knowledge discovery in single sequences. Frequency based knowledge discovery in single sequences tends to be unreliable since different resulting sets may be obtained from a same sequence when different frequency metrics are adopted. In this chapter, we investigate subsequence frequency measurement and its impact on the reliability of knowledge discovery in single sequences. We analyse seven previous frequency metrics, identify their inherent inaccuracies, and explore their impacts on two kinds of knowledge discovered from single sequences, frequent episodes and episode rules. We further give three suggestions for frequency metrics and introduce a new frequency metric in order to improve the reliability. Empirical evaluation reveals the inaccuracies and verifies our findings.
ISBN 9781461419020
9781461419037
Language eng
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 890202 Application Tools and System Utilities
HERDC Research category B1 Book chapter
Copyright notice ©2012, Springer Science+Business Media, LLC
Persistent URL http://hdl.handle.net/10536/DRO/DU:30043152

Document type: Book Chapter
Collection: School of Information Technology
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