Man-Soon Kim
ABSTRACT
This paper discusses effective processing of subsequence matching under time warping in time-series databases. Time warping is a transformation that enables finding of sequences with similar patterns even when they are of different lengths. Through a preliminary experiment, we first point out that Naive-Scan, a basic method for processing of subsequence matching under time warping, has its performance bottleneck in the CPU processing step. For optimizing this step, in this paper, we propose a novel method that eliminates all possible redundant calculations. It is verified that this method is not only an optimal one for processing Naive-Scan, but also does not incur any false dismissals. Our experimental results showed that the proposed method can make great improvement in performance of subsequence matching under time warping. Especially, Naive-Scan, which has been known to show the worst performance, performs much better than LB-Scan as well as ST-Filter in all the cases by employing the proposed method for CPU processing. This result is interesting and valuable in that the performance inversion among Naive-Scan, LB-Scan, and ST-Filter has occurred by optimizing the CPU processing step, which is their common performance bottleneck.
- Agrawal, R., Faloutsos, C., and Swami, A. Efficient Similarity Search in Sequence Databases, In Proceedings of International Conference on Foundations of Data Organization and Algorithms (FODO '93) (Oct. 1993), 69--84. Google Scholar
Digital Library
- Agrawal, R. et al. Fast Similarity Search in the Presence of Noise, Scaling, and Translation in Time-Series Databases, In Proceedings of International Conference on Very Large Data Bases, (VLDB '95) (Sept. 1995), 490--501. Google ScholarDigital Library
- Berndt, D. J. and Clifford, J. Finding Patterns in Time Series: A Dynamic Programming Approach, In Proceedings of International Conference on Advances in Knowledge Discovery and Data Mining (KDD '96) (Mar. 1996), 229--248. Google ScholarDigital Library
- Chu, K. K. W. and Wong, M. H. Fast Time-Series Searching with Scaling and Shifting, In Proceedings of International Conference on Principles of Database Systems (ACM PODS '99) (May 1999), 237--248. Google ScholarDigital Library
- Das, G., Gunopulos, D., and Mannila, H. Finding Similar Time Series, In Proceedings of European Symposium on Principles of Data Mining and Knowledge Discovery, (PKDD '97) (May 1997), 88--100. Google ScholarDigital Library
- Faloutsos, C., Ranganathan, M., and Manolopoulos, Y. Fast Subsequence Matching in Time-series Databases, In Proceedings of International Conference on Management of Data, (ACM SIGMOD '94) (May 1994), 419--429. Google ScholarDigital Library
- Kim, S. W., Park, S. H., and Chu, W. W. Efficient Processing of Similarity Search under Time Warping in Sequence Databases: An Index-Based Approach, Information Systems, 29, 5, (Mar. 2004), 405--420. Google ScholarDigital Library
- Loh, W. K., Kim, S. W., and Whang, K. Y. Index Interpolation: An Approach for Subsequence Matching Supporting Normalization Transform in Time-Series Databases, In Proceedings of ACM International Conference on Information and Knowledge Management (ACM CIKM '00) (Oct. 2000), 480--487. Google ScholarDigital Library
- Loh, W. K., Kim, S. W., and Whang, K. Y. Index Interpolation: A Subsequence Matching Algorithm Supporting Moving Average Transform of Arbitrary Order in Time-Series Databases, IEICE Trans. on Information and Systems, E84-D, 1, (Mar. 2001), 76--86.Google Scholar
- Park, S. H. et al. Efficient Searches for Similar Subsequences of Difference Lengths in Sequence Databases, In Proceedings of IEEE International Conference on Data Engineering (IEEE ICDE '00) (Mar. 2000), 23--32. Google ScholarDigital Library
- Park, S. H., Kim, S. W., Cho, J. S., and Padmanabhan, S. Prefix-Querying: An Approach for Effective Subsequence Matching Under Time Warping in Sequence Databases, In Proceedings of ACM International Conference on Information and Knowledge Management (ACM CIKM '01), (Oct. 2001), 255--262. Google ScholarDigital Library
- Park, S. H. private communication, 2003.Google Scholar
- Rafiei, D. On Similarity-Based Queries for Time Series Data, In In Proceedings of IEEE International Conference on Data Engineering (IEEE ICDE '99) (Mar. 1999), 410--417. Google ScholarDigital Library
- Yi, B. K., Jagadish, H. V., and Faloutsos, C. Efficient Retrieval of Similar Time Sequences Under Time Warping, In Proceedings of IEEE International Conference on Data Engineering (IEEE ICDE '98) (Mar. 1998) 201--208. Google ScholarDigital Library
- Kim, M. S., Kim, S. W., and Shin, M. Y. Subsequence Matching Under Time-Warping in Time-Series Databases: Observation, Optimization, and Performance Results, Unpublished Manuscript, 2004.Google Scholar
Index Terms
- Optimization of subsequence matching under time warping in time-series databases
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