Prefix similarity search in time series databases and a scheme for its efficient evaluation

Yaokai Feng, Kunihiko Kaneko

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The researches on time series databases have been one of the hot topics in database community for a long time. Of such researches, similarity search (query-by-content) has been drawn much interest. The existing similarity search is classified into whole matching and subsequence matching. In this study, we propose a new kind of matching, Prefix Similarity Search, for the first time, which is useful in many applications including clustering and prediction. And a scheme is also presented for its efficient evaluation.

Original languageEnglish
Title of host publicationWMSCI 2008 - The 12th World Multi-Conference on Systemics, Cybernetics and Informatics, Jointly with the 14th International Conference on Information Systems Analysis and Synthesis, ISAS 2008 - Proc.
Pages144-149
Number of pages6
Publication statusPublished - Dec 1 2008
Event12th World Multi-Conference on Systemics, Cybernetics and Informatics, WMSCI 2008, Jointly with the 14th International Conference on Information Systems Analysis and Synthesis, ISAS 2008 - Orlando, FL, United States
Duration: Jun 29 2008Jul 2 2008

Publication series

NameWMSCI 2008 - The 12th World Multi-Conference on Systemics, Cybernetics and Informatics, Jointly with the 14th International Conference on Information Systems Analysis and Synthesis, ISAS 2008 - Proc.
Volume6

Other

Other12th World Multi-Conference on Systemics, Cybernetics and Informatics, WMSCI 2008, Jointly with the 14th International Conference on Information Systems Analysis and Synthesis, ISAS 2008
CountryUnited States
CityOrlando, FL
Period6/29/087/2/08

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications

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