NDLI: Diagnosing Similarity of Oscillation Trends in Time Series

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Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007)

Seventh IEEE International Conference on Data Mining Workshops - Title

Seventh IEEE International Conference on Data Mining Workshops - Copyright

Workshops and Organizations

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Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06)

Diagnosing Similarity of Oscillation Trends in Time Series

Content Provider	IEEE Xplore Digital Library
Author	Mariote, Leonardo E. Medeiros, Claudia Bauzer da S.Torres, Ricardo
Copyright Year	2007
Abstract	Sensor networks have increased the amount and variety of temporal data available, requiring the definition of new techniques for data mining. Related research typically ad- dresses the problems of indexing, clustering, classification, summarization, and anomaly detection. They present many ways for describing and comparing time series, but they fo- cus on their values. This paper concentrates on a new as- pect - that of describing oscillation patterns. It presents a technique for time series similarity search, based on multi- ple temporal scales, defining a descriptor that uses the an- gular coefficients from a linear segmentation of the curve that represents the evolution of the analyzed series. Prelim- inary experiments with real datasets showed that our ap- proach correctly characterizes the oscillation of time series.
Starting Page	643
Ending Page	648
File Size	260236
Page Count	6
File Format	PDF
ISBN	9780769530192
DOI	10.1109/ICDMW.2007.28
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-10-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Temperature sensors Data analysis Conferences Time series analysis Feature extraction Spatial databases Computer networks Data mining Indexing Information analysis
Content Type	Text
Resource Type	Article

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