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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/9785

Title: Spatio-Temporal Symbolization of Multidimensional Time Series
Authors: Hidaka, Shohei
Yu, Chen
Keywords: time series symbolization
generating partition
dynamical system
dimension selection
heterogeneous multivariate time series
Issue Date: 2010-12-13
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Magazine name: 2010 IEEE International Conference on Data Mining Workshops (ICDMW)
Start page: 249
End page: 256
DOI: 10.1109/ICDMW.2010.86
Abstract: The present study proposes a new symbolization algorithm for multidimensional time series. We view temporal sequences as observed data generated by a dynamical system, and therefore the goal of symbolization is to estimate symbolic sequences that minimize loss of information, which is called generating partition in nonlinear physics. In order to utilize the theoretical property of symbol dynamics in data mining, our algorithm estimates symbols on multivariate time series by integrating both spatial and temporal information and selecting those dimensions in multidimensional time series containing useful information. Probabilistic symbolic sequences derived from our symbolization method can be used in various supervised and unsupervised data-mining tasks. To demonstrate this, the algorithm is evaluated by applying it to both simulated data and a real-world dataset. In both cases, the new algorithm outperforms its alternative approaches.
Rights: Copyright © 2010 IEEE. Reprinted from 2010 IEEE International Conference on Data Mining Workshops (ICDMW), 2010, 249-256. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of JAIST's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
URI: http://hdl.handle.net/10119/9785
Material Type: author
Appears in Collections:a11-1. 会議発表論文 (Conference Papers)

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