NDLI: Time Series Analysis Using the Concept of Adaptable Threshold Similarity

Content Provider	IEEE Xplore Digital Library
Author	Assfalg, J. Kriegel, H.-P. Kroger, P. Kunath, P. Pryakhin, A. Renz, M.
Copyright Year	2006
Description	Author affiliation: Inst. for Informatics, Univ. of Munich (Assfalg, J.; Kriegel, H.-P.; Kroger, P.; Kunath, P.; Pryakhin, A.; Renz, M.)
Abstract	The issue of data mining in time series databases is of utmost importance for many practical applications and has attracted a lot of research in the past years. In this paper, we focus on the recently proposed concept of threshold similarity which compares the time series based on the time frames within which they exceed a user-defined amplitude threshold tau. We propose a novel approach for cluster analysis of time series based on adaptable threshold similarity. The most important issue in threshold similarity is the choice of the threshold tau. Thus, the threshold tau is automatically adapted to the characteristics of a small training dataset using the concept of support vector machines. Thus, the optimal tau is learned from a small training set in order to yield an accurate clustering of the entire time series database. In our experimental evaluation we demonstrate that our cluster analysis using adaptable threshold similarity can be successfully applied to many scientific real-world data mining applications
Starting Page	251
Ending Page	260
File Size	422692
Page Count	10
File Format	PDF
ISBN	0769525903
ISSN	15516393
DOI	10.1109/SSDBM.2006.53
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-07-03
Publisher Place	Austria
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Time series analysis Databases Data mining Informatics Support vector machines Astronomy Pattern analysis Extraterrestrial measurements Particle measurements Time measurement
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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