Efficient pattern matching of multidimensional sequences

Sangjun Lee, Kyoungsu Oh, Dongseop Kwon, Wonik Choi, Jiman Hong, Jongmoo Choi, Donghee Lee

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

We address the problem of the similarity search in large multidimensional sequence databases. Most of previous work focused on similarity matching and retrieval of one-dimensional sequences. However, many new applications such as weather data or music databases need to handle multidimensional sequences. In this paper, we present the efficient search method for finding similar sequences to a given query sequence in multidimensional sequence databases. The proposed method can efficiently reduce the search space and guarantees no false dismissals. We give preliminary experimental results to show the effectiveness of the proposed method.

Original languageEnglish
Title of host publicationRough Sets, Fuzzy Sets, Data Mining, and Granular Computing - 10th International Conference, RSFDGrC 2005, Proceedings
PublisherSpringer Verlag
Pages202-210
Number of pages9
ISBN (Print)3540286608, 9783540286608
DOIs
StatePublished - 2005
Event10th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2005 - Regina, Canada
Duration: 31 Aug 20053 Sep 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3642 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2005
Country/TerritoryCanada
CityRegina
Period31/08/053/09/05

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