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http://dx.doi.org/10.3745/KIPSTD.2003.10D.4.577

Shape-Based Subsequence Retrieval Supporting Multiple Models in Time-Series Databases  

Won, Jung-Im (한림대학교 대학원 컴퓨터공학과)
Yoon, Jee-Hee (한림대학교 정보통신공학부)
Kim, Sang-Wook (한양대학교 정보통신공학부)
Park, Sang-Hyun (포항공과대학교 컴퓨터공학과)
Publication Information
The KIPS Transactions:PartD / v.10D, no.4, 2003 , pp. 577-590 More about this Journal
Abstract
The shape-based retrieval is defined as the operation that searches for the (sub) sequences whose shapes are similar to that of a query sequence regardless of their actual element values. In this paper, we propose a similarity model suitable for shape-based retrieval and present an indexing method for supporting the similarity model. The proposed similarity model enables to retrieve similar shapes accurately by providing the combination of various shape-preserving transformations such as normalization, moving average, and time warping. Our indexing method stores every distinct subsequence concisely into the disk-based suffix tree for efficient and adaptive query processing. We allow the user to dynamically choose a similarity model suitable for a given application. More specifically, we allow the user to determine the parameter p of the distance function $L_p$ when submitting a query. The result of extensive experiments revealed that our approach not only successfully finds the subsequences whose shapes are similar to a query shape but also significantly outperforms the sequence search.
Keywords
Sequence Databases; Similarity Search; Shape-Based Retrieval; Indexing; Time Warping;
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