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http://dx.doi.org/10.3745/KIPSTD.2005.12D.3.355

Effectiveness Evaluations of Subsequence Matching Methods Using KOSPI Data  

Yoo Seung Keun (숭실대학교 대학원 컴퓨터학과)
Lee Sang Ho (숭실대학교 컴퓨터학부)
Publication Information
The KIPS Transactions:PartD / v.12D, no.3, 2005 , pp. 355-364 More about this Journal
Abstract
Previous researches on subsequence matching have been focused on how to make indexes in order to speed up the matching time, and do not take into account the effectiveness issues of subsequence matching methods. This paper considers the effectiveness of subsequence matching methods and proposes two metrics for effectiveness evaluations of subsequence matching algorithms. We have applied the proposed metrics to Korean stock data and five known matching algorithms. The analysis on the empirical data shows that two methods (i.e., the method supporting normalization, and the method supporting scaling and shifting) outperform the others in terms of the effectiveness of subsequence matching.
Keywords
Data Mining; Data Sequence; Time-series Data; Effectiveness Evaluation;
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1 D. Rafiei and A. Mendelzon, 'Similarity-Based Queries for Time Series Data,' In Proceedings of the International Conference on Management of Data, pp.13-24, 1997   DOI
2 김상욱, 박상현, '시퀀스 데이터베이스에서 타임 워핑을 지원하는 효과적인 유사 검색 기법', 정보과학회 논문지, 제28권 제4호, pp.643-654, 2001
3 노웅기, 김상욱, 황규영, '시계열 데이터베이스에서 인덱스 보간법을 기반으로 정규화변환을 지원하는 서브시퀀스 매칭 알고리즘', 정보과학회 논문지, 제28권 제2호, pp.217-232, 2001
4 Y. S. Moon, K. Y. Whang and W. K. Loh, 'Duality-Based Subsequence Matching in Time-Series Databases,' In Proceedings of the International Conference on Data Engineering, pp.263-272, 2001
5 S. H. Park, W. W. Chu, J. H. Yoon and C. Hsu, 'Efficient Searches for Similar Subsequence of Different Lengths in Sequence Databases,' In Proceedings of the International Conference on Data Engineering, pp.23-32, 2000
6 E. Keogh, J. Lin and W. Tuppel, 'Clustering of Time Series Subsequence is Meaningless : Implication for Previous and Future Research,' In Proceedings of the third IEEE International Conference on Data Mining, pp.115-125, 2003
7 R. R. Korfhage, 'Information Storage and Retrieval,' Wiley Press, 1997
8 W. K. Loh, S. W. Kim and K. Y. Whang, 'Index Interpolation : An Approach for Subsequence Matching Supporting Normalization Transform in Time-Series Databases,' In Proceedings of the International Conference on Information and Knowledge Management, pp.480-487, 2000
9 K. K. W. Chu and M. H. Wong, 'Fast Time-Series Searching with Scaling and Shifting,' In Proceeding of the International Symposium on Principles of Databases Systems, pp.237-248, 1999   DOI
10 C. Faloutsos, M. Ranganathan and Y. Manolopoulos, 'Fast Subsequence Matching in Time-Series Databases,' In Proceedings of the International Conference on Management of Data, pp.419-429, 1994   DOI   ScienceOn
11 D. Q. Goldin and P. C. Kanellakis, 'On Similarity Queries for Time-Series Data: Constraint Specification and Implementation,' In Proceedings of the International Conference on Principles of Data Mining and Knowledge Discovery, pp. 88-100, 1997
12 R. Agrawal, C. Faloutsos and A. Swami, 'Efficient Similarity Search in Sequence Databases,' In Proceedings of the International Conference on Foundations of Data Organization and Algorithms, pp.69-84, 1993
13 D. J. Bernidt and J. Clifford, 'Finding Patterns in Time Series : A Dynamic Programming Approach,' Advances in Knowledge Discovery and Data mining, AAA/MIT Press, pp.229-248, 1996