A study on the accuracy of frequency measures and its impact on knowledge discovery in single sequences

Gan, Min and Dai, Honghua 2010, A study on the accuracy of frequency measures and its impact on knowledge discovery in single sequences, in ICDMW 2010 : Proceedings of 10th IEEE International Conference on Data Mining Workshops, IEEE Computer Society, Sydney, NSW, pp. 859-866.

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Title A study on the accuracy of frequency measures and its impact on knowledge discovery in single sequences
Author(s) Gan, Min
Dai, Honghua
Conference name International Conference on Data Mining Workshops (10th : 2010 : Sydney, N.S.W.)
Conference location Sydney, NSW
Conference dates 14 Dec. 2010
Title of proceedings ICDMW 2010 : Proceedings of 10th IEEE International Conference on Data Mining Workshops
Editor(s) Fan, Wei
Hsu, Wynne
Webb, Geoffrey I.
Liu, Bing
Zhang, Chengqi
Gunopulos, Dimitrios
Wu, Xindong
Publication date 2010
Conference series International Conference on Data Mining
Start page 859
End page 866
Total pages 8
Publisher IEEE Computer Society
Place of publication Sydney, NSW
Keyword(s) frequency measures
episodes
single sequences
knowlede discovery
Summary In knowledge discovery in single sequences, different results could be discovered from the same sequence when different frequency measures are adopted. It is natural to raise such questions as (1) do these frequency measures reflect actual frequencies accurately? (2) what impacts do frequency measures have on discovered knowledge? (3) are discovered results accurate and reliable? and (4) which measures are appropriate for reflecting frequencies accurately? In this paper, taking three major factors (anti-monotonicity, maximum-frequency and window-width restriction) into account, we identify inaccuracies inherent in seven existing frequency measures, and investigate their impacts on the soundness and completeness of two kinds of knowledge, frequent episodes and episode rules, discovered from single sequences. In order to obtain more accurate frequencies and knowledge, we provide three recommendations for defining appropriate frequency measures. Following the recommendations, we introduce a more appropriate frequency measure. Empirical evaluation reveals the inaccuracies and verifies our findings. 
ISBN 9780769542577
Language eng
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1 Full written paper - refereed
HERDC collection year 2010
Copyright notice ©2010, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30035409

Document type: Conference Paper
Collection: School of Information Technology
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