Shape-based retrieval of similar subsequences in time-series databases

Sang Wook Kim, Jeehee Yoon, Sanghyun Park, Tae Hoon Kim

Research output: Contribution to conferencePaper

14 Citations (Scopus)

Abstract

This paper deals with the problem of shape-based retrieval in time-series databases. The shape-based retrieval is defined as the operation that searchers for the (sub)sequences whose shapes are similar to that of a given query sequence. In this paper, we propose an effective an efficient approach for shape-based retrieval of subsequences. We first introduce a new similarity model for shape-based retrieval that supports various combinations of transformations such as shifting, scaling, moving average, and time warping. For efficient processing of the shape-based retrieval, we also propose the indexing and query processing methods. To verify the superiority of our approach, we perform extensive experiments with the real-world S&P 500 stock data. The results reveal that our approach successfully finds all the subsequences that have the shapes similar to that of the query sequence, and also achieves significant speedup over the sequential scan method.

Original languageEnglish
Pages438-445
Number of pages8
DOIs
Publication statusPublished - 2002
EventApplied Computing 2002: Proceeedings of the 2002 ACM Symposium on Applied Computing - Madrid, Spain
Duration: 2002 Mar 112002 Mar 14

Other

OtherApplied Computing 2002: Proceeedings of the 2002 ACM Symposium on Applied Computing
CountrySpain
CityMadrid
Period02/3/1102/3/14

All Science Journal Classification (ASJC) codes

  • Software

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    Kim, S. W., Yoon, J., Park, S., & Kim, T. H. (2002). Shape-based retrieval of similar subsequences in time-series databases. 438-445. Paper presented at Applied Computing 2002: Proceeedings of the 2002 ACM Symposium on Applied Computing, Madrid, Spain. https://doi.org/10.1145/508791.508874