skip to main content
10.1145/303976.304000acmconferencesArticle/Chapter ViewAbstractPublication PagespodsConference Proceedingsconference-collections
Article
Free Access

Fast time-series searching with scaling and shifting

Authors Info & Claims
Published:01 May 1999Publication History
First page image

References

  1. 1.R. Agrawal, C. Faloutsos, and A. Swami. E',fficient Similarity Search in Sequence Databases. in international Conference on Foundations of Data Organization and Algorithms, pages 69-84, 1993. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. 2.C. Faloutsos, M. Ranganathan, and Y. Manolopoulos. Fast Subsequence Matching in Time-Series Databases. In Proc. of the A CM SIGMOD Conference on Management of Data, pages 419-429, 1994. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. 3.I~. Agrawal, K.-I. Lin, H. S. Sawhney, and K. Shim. Fast Similarity Search in the Presence of Noise, Scaling, and Translation in Time-Series Databases. In Proc. of the 21st VLDB Conference, pages 490-501, 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. 4.H. V. Jagadish, A. O. Mendelzon, and T. Milo. Similarity-Based Queries. In Symposium on Principles of Database Systems, pages 36-45, 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. 5.D. Rafiei and A. Mendelzon. Similarity-Based Queries for Time Series Data. in Proc. of the A CM SIGMOD Conference on Management of Data, pages 13-25, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. 6.D. Q. Goldin and P. C. Kanellakis. On similarity queries for time-series data: constraint specification and implementation. In 1st Intl. Conf. on the Principles and Practice of Constraint Programming, pages 137-153, 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. 7.H. Shatkay and S. B. Zdonik. Approximate Queries and Representations for Large Data Sequences. In international Conference on Data Engineering, pages 536-545, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. 8.C.-S. Li, P. S. Yu, and V. Castelli. Similarity Search Algorithm for Databases of Long Sequences. In International Conference on Data Engineering, pages 546-553, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. 9.T. Bozkaya, N. Yazdani, and Z. M. Ozsoyoglu. Matching and Indexing Sequences of Different Lengths. in Proc. l gg7 A CM CIKM, Sixth International Conference on Information and Knowledge Management, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. 10.B. Yi, H. V. Jagadish, and C. Faloutsos. Efficient Retrieval of Similar Time Sequences Under Time Warping. In International Conference on Data Engineering, 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. 11.S. K. Lain and M. H. Wong. A Fast Signature Algorithm for Sequence Data Searching. In The Third International Workshop on Next Generation Information Technologies and Systems, pages 172-181, 1997.Google ScholarGoogle Scholar
  12. 12.S.K. Lain and M.H. Wong. A Fast Projection Algorithm for Sequence Data Searching. Data and Knowledge Engineering, 28:321- 339, 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. 13.K.W. Chu, S.K. Lam, and M.H. Wong. An Efficient Hash-based Algorithm for Sequence Data Searching. The Computer Journal, 41:402-415, 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. 14.K. P. Chan and W. C. Fu. Efficient Time Series Matching by Wavelets. In International Conference on Data Engineering, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. 15.B. Bollob~s, G. Das, D. Gunopulos, and H. Mannila. Time-Series Similarity Problems and Well-Separated Geometric Sets. in 13th Annual A CM Symposium on Computational Geometry, pages 454-456, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. 16.N. Beckmann, H.-P. Kriegel, R. Schneider, and B. Seeger. The R*-tree: an efficient and robust access method for points and rectangles. In Proc. o/the A CM SIGMOD Conference on Management of Data, pages 322-331, 1990. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. 17.K. Shim, R. Srikant, and R. Agrawal. A Fast Algorithm for high-dimensional Similarity Joins. Technical report, IBM Almaden Research Center, 1996.Google ScholarGoogle Scholar
  18. 18.T. Sellis, N. Roussopoulos, and C. Faloutsos. The R+ tree: a dynamic index for multidimensional objects. In Proc. of the 13th VLDB Conference, 1987. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. 19.G. Das, D. Gunopulos, and H. Mannila. Finding similar time series. In 1st European Symposium on Principles of Data Mining and Knowledge Discovery, pages 88-100, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. 20.K. V. R. Kanth, D. Agrawal, and A. K. Singh. Dimensionality-Reduction for Similarity Searching in Dynamic Databases. In Proc. of the A CM SIGMOD Conference on Management of Data, pages 166-176, 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. 21.H. F. Davis and A. D. Snider. Introduction to Vector Analysis. Win. C. Brown Publishers, 1995.Google ScholarGoogle Scholar
  22. 22.A. Guttman. R-tree: a dynamic index structure for spatial searching. In Proc. of the A CM SIGMOD Conference on Management of Data, pages 47-57, 1984. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. 23.S. Berchtold, D. A. Keim, and H.-P. Kriegel. The X-tree : An Index Structure for High- Dimensional Data. In Proc. of the 22th VLDB Conference, pages 28-39, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. 24.J. B. Fraleigh and R. A. Beauregard. Linear Algebra. Addison Wesley, 1995.Google ScholarGoogle Scholar
  25. 25.A. Watt. 3D Computer Graphics. Addison Wesley, 1993. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. 26.N. Katayama and S. Satoh. The SR-tree: All Index Structure for High-Dimensional Nearest Neighbor Queries. In Proc. of the A CM SIGMOD Conference on Management of Data, pages 369-380, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Fast time-series searching with scaling and shifting

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Conferences
          PODS '99: Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
          May 1999
          374 pages
          ISBN:1581130627
          DOI:10.1145/303976

          Copyright © 1999 ACM

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 1 May 1999

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • Article

          Acceptance Rates

          PODS '99 Paper Acceptance Rate32of116submissions,28%Overall Acceptance Rate642of2,707submissions,24%

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader