Shape-based retrieval in time-series databases

Sang Wook Kim, Jeehee Yoon, Sanghyun Park, Jung Im Won

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

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 multiple 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 Lp 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 sequential scan method.

Original languageEnglish
Pages (from-to)191-203
Number of pages13
JournalJournal of Systems and Software
Volume79
Issue number2
DOIs
Publication statusPublished - 2006 Feb

Bibliographical note

Funding Information:
This work has been supported by Korea Research Foundation with Grant KRF-2003-041-D00486, the IT Research Center via Kangwon National University, and the University Research Program (C1-2002-146-0-3) of IITA. Sang-Wook Kim would like to thank Jung-Hee Seo, Suk-Yeon Hwang, Grace (Joo-Young) Kim, and Joo-Sung Kim for their encouragement and support.

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems
  • Hardware and Architecture

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