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Sensor Time Series Association Rule Discovery Based on Modified Discretization Method
Donghua Univ, Sch Comp Sci & Technol, Shanghai, Peoples R China.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems.
Donghua Univ, Sch Comp Sci & Technol, Shanghai, Peoples R China.
Donghua Univ, Sch Comp Sci & Technol, Shanghai, Peoples R China.
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2016 (English)In: 2016 FIRST IEEE INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATION AND THE INTERNET (ICCCI 2016), IEEE, 2016, 196-202 p., 7778907Conference paper, (Refereed)
Abstract [en]

Association rule discovery from sensor time series is a challenge. Because the time series has high dimensional, numerical and continuous nature. However the general association methods can only deal with data which are symbolic and discrete. And the general association methods have high processing time consumption when the data have high dimension. So a useful framework is proposed, which is pre-processing, representation, discretization and temporal association mining. In the discretization section, a modified discretization method is proposed which can combine the advantages of other methods, such as piecewise aggregate approximation (PAA), knee point selection, symbolic aggregate approximation (SAX) and monotonicity feature extraction. In the association section, a modified Apriori algorithm is proposed to discover special patterns and normal rules.

Place, publisher, year, edition, pages
IEEE, 2016. 196-202 p., 7778907
Keyword [en]
sensor time series, discretization method, temporal association method
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:miun:diva-29995ISI: 000390712100043Scopus ID: 2-s2.0-85010457770ISBN: 978-1-4673-8515-2 (print)OAI: oai:DiVA.org:miun-29995DiVA: diva2:1071697
Conference
1st IEEE International Conference on Computer Communication and the Internet (ICCCI), OCT 13-15, 2016, Wuhan, PEOPLES R CHINA
Available from: 2017-02-06 Created: 2017-02-06 Last updated: 2017-02-14Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf