Abstract
This paper presents techniques for discovering and matching rules with elastic patterns. Elastic patterns are ordered lists of elements that can be stretched along the time axis. Elastic patterns are useful for discovering rules from data sequences with different sampling rates. For fast discovery of rules whose heads (left-hand sides) and bodies (right-hand sides) are elastic patterns, we construct a trimmed suffix tree from succinct forms of data sequences and keep the tree as a compact representation of rules. The trimmed suffix tree is also used as an index structure for finding rules matched to a target head sequence. When matched rules cannot be found, the concept of rule relaxation is introduced. Using a cluster hierarchy and relaxation error as a new distance function, we find the least relaxed rules that provide the most specific information on a target head sequence. Experiments on synthetic data sequences reveal the effectiveness of our proposed approach.
| Original language | English |
|---|---|
| Pages (from-to) | 75-90 |
| Number of pages | 16 |
| Journal | Fundamenta Informaticae |
| Volume | 47 |
| Issue number | 1-2 |
| Publication status | Published - 2001 Jul 1 |
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All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Algebra and Number Theory
- Information Systems
- Computational Theory and Mathematics
Cite this
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Discovering and matching elastic rules from sequence databases. / Hyun, Park Sang; Chu Wesley, W.
In: Fundamenta Informaticae, Vol. 47, No. 1-2, 01.07.2001, p. 75-90.Research output: Contribution to journal › Article
TY - JOUR
T1 - Discovering and matching elastic rules from sequence databases
AU - Hyun, Park Sang
AU - Chu Wesley, W.
PY - 2001/7/1
Y1 - 2001/7/1
N2 - This paper presents techniques for discovering and matching rules with elastic patterns. Elastic patterns are ordered lists of elements that can be stretched along the time axis. Elastic patterns are useful for discovering rules from data sequences with different sampling rates. For fast discovery of rules whose heads (left-hand sides) and bodies (right-hand sides) are elastic patterns, we construct a trimmed suffix tree from succinct forms of data sequences and keep the tree as a compact representation of rules. The trimmed suffix tree is also used as an index structure for finding rules matched to a target head sequence. When matched rules cannot be found, the concept of rule relaxation is introduced. Using a cluster hierarchy and relaxation error as a new distance function, we find the least relaxed rules that provide the most specific information on a target head sequence. Experiments on synthetic data sequences reveal the effectiveness of our proposed approach.
AB - This paper presents techniques for discovering and matching rules with elastic patterns. Elastic patterns are ordered lists of elements that can be stretched along the time axis. Elastic patterns are useful for discovering rules from data sequences with different sampling rates. For fast discovery of rules whose heads (left-hand sides) and bodies (right-hand sides) are elastic patterns, we construct a trimmed suffix tree from succinct forms of data sequences and keep the tree as a compact representation of rules. The trimmed suffix tree is also used as an index structure for finding rules matched to a target head sequence. When matched rules cannot be found, the concept of rule relaxation is introduced. Using a cluster hierarchy and relaxation error as a new distance function, we find the least relaxed rules that provide the most specific information on a target head sequence. Experiments on synthetic data sequences reveal the effectiveness of our proposed approach.
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UR - http://www.scopus.com/inward/citedby.url?scp=0035401768&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:0035401768
VL - 47
SP - 75
EP - 90
JO - Fundamenta Informaticae
JF - Fundamenta Informaticae
SN - 0169-2968
IS - 1-2
ER -