Abstract
This paper investigates the subsequence searching problem under time warping in sequence databases. Time warping enables to find sequences with similar changing patterns even when they are of different lengths. Our work is motivated by the observation that subsequence searches slow down quadratically as the total length of data sequences increases. To resolve this problem, we propose the Segment-Based Approach for Subsequence Searches (SBASS), which modifies the similarity measure from time warping to piece-wise time warping and limits the number of possible subsequences to be compared with a query sequence. For efficient retrieval of similar subsequences, we extract feature vectors from all data segments exploiting their mono-tonically changing properties, and build a multi-dimensional index such as R-tree or R∗-tree. Using this index, queries are processed with four steps: 1) index filtering, 2) feature filtering, 3) successor filtering, and 4) post-processing. The effectiveness of our approach is verified through experiments on synthetic data sets.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 2001 ACM Symposium on Applied Computing, SAC 2001 |
| Publisher | Association for Computing Machinery |
| Pages | 248-252 |
| Number of pages | 5 |
| ISBN (Print) | 1581132875, 9781581132878 |
| DOIs | |
| Publication status | Published - 2001 Mar 1 |
| Event | 2001 ACM Symposium on Applied Computing, SAC 2001 - Las Vegas, United States Duration: 2001 Mar 11 → 2001 Mar 14 |
Publication series
| Name | Proceedings of the ACM Symposium on Applied Computing |
|---|
Other
| Other | 2001 ACM Symposium on Applied Computing, SAC 2001 |
|---|---|
| Country | United States |
| City | Las Vegas |
| Period | 01/3/11 → 01/3/14 |
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All Science Journal Classification (ASJC) codes
- Software
Cite this
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Segment-based approach for subsequence searches in sequence databases. / Park, Sang Hyun; Kim, Sang Wook; Chu, Wesley W.
Proceedings of the 2001 ACM Symposium on Applied Computing, SAC 2001. Association for Computing Machinery, 2001. p. 248-252 (Proceedings of the ACM Symposium on Applied Computing).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Segment-based approach for subsequence searches in sequence databases
AU - Park, Sang Hyun
AU - Kim, Sang Wook
AU - Chu, Wesley W.
PY - 2001/3/1
Y1 - 2001/3/1
N2 - This paper investigates the subsequence searching problem under time warping in sequence databases. Time warping enables to find sequences with similar changing patterns even when they are of different lengths. Our work is motivated by the observation that subsequence searches slow down quadratically as the total length of data sequences increases. To resolve this problem, we propose the Segment-Based Approach for Subsequence Searches (SBASS), which modifies the similarity measure from time warping to piece-wise time warping and limits the number of possible subsequences to be compared with a query sequence. For efficient retrieval of similar subsequences, we extract feature vectors from all data segments exploiting their mono-tonically changing properties, and build a multi-dimensional index such as R-tree or R∗-tree. Using this index, queries are processed with four steps: 1) index filtering, 2) feature filtering, 3) successor filtering, and 4) post-processing. The effectiveness of our approach is verified through experiments on synthetic data sets.
AB - This paper investigates the subsequence searching problem under time warping in sequence databases. Time warping enables to find sequences with similar changing patterns even when they are of different lengths. Our work is motivated by the observation that subsequence searches slow down quadratically as the total length of data sequences increases. To resolve this problem, we propose the Segment-Based Approach for Subsequence Searches (SBASS), which modifies the similarity measure from time warping to piece-wise time warping and limits the number of possible subsequences to be compared with a query sequence. For efficient retrieval of similar subsequences, we extract feature vectors from all data segments exploiting their mono-tonically changing properties, and build a multi-dimensional index such as R-tree or R∗-tree. Using this index, queries are processed with four steps: 1) index filtering, 2) feature filtering, 3) successor filtering, and 4) post-processing. The effectiveness of our approach is verified through experiments on synthetic data sets.
UR - http://www.scopus.com/inward/record.url?scp=77952145570&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77952145570&partnerID=8YFLogxK
U2 - 10.1145/372202.372334
DO - 10.1145/372202.372334
M3 - Conference contribution
AN - SCOPUS:77952145570
SN - 1581132875
SN - 9781581132878
T3 - Proceedings of the ACM Symposium on Applied Computing
SP - 248
EP - 252
BT - Proceedings of the 2001 ACM Symposium on Applied Computing, SAC 2001
PB - Association for Computing Machinery
ER -