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2000
IEEE

Similarity Search for Multidimensional Data Sequences

12 years 2 months ago
Similarity Search for Multidimensional Data Sequences
Time-series data, which are a series of one-dimensional real numbers, have been studied in various database applications. In this paper, we extend the traditional similarity search methods on time-series data to support a multidimensional data sequence, such as a video stream. We investigate the problem of retrieving similar multidimensional data sequences from a large database. To prune irrelevant sequences in a database, we introduce correct and efficient similarity functions. Both data sequences and query sequences are partitioned into subsequences, and each of them is represented by a Minimum Bounding Rectangle (MBR). The query processing is based upon these MBRs, instead of scanning data elements of entire sequences. Our method is designed (1) to select candidate sequences in a database, and (2) to find the subsequences of a selected sequence, each of which falls under the given threshold. The latter is of special importance in the case of retrieving subsequences from large and c...
Seok-Lyong Lee, Seok-Ju Chun, Deok-Hwan Kim, Ju-Ho
Added 01 Nov 2009
Updated 01 Nov 2009
Type Conference
Year 2000
Where ICDE
Authors Seok-Lyong Lee, Seok-Ju Chun, Deok-Hwan Kim, Ju-Hong Lee, Chin-Wan Chung
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