Variable step algorithm for sub-trend sequence searching

Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science)

Volumn 38, Issue 12, 2004, Pages 1566-1569

  Wang, Da ^a   Rong, Gang ^a   Li, Hong Liang ^a  

^a STATE KEY LABORATORY OF INDUSTRIAL CONTROL TECHNOLOGY   (China)

Author keywords

Data mining; Sub sequence search; Trend sequence

Indexed keywords

COMPUTER SIMULATION; LEARNING ALGORITHMS; NUMERICAL ANALYSIS; TIME SERIES ANALYSIS;

PIECEWISE TREND SEQUENCE (PTS); SUBSEQUENCE SEARCH; THEORETIC ANALYSIS; TIME SERIES DYNAMIC FEATURE ANALYSIS; TREND SEQUENCE; VARIABLE INCREMENTAL STEP LENGTH; VARIABLE STEP ALGORITHM;

DATA MINING;

EID: 13644273612     PISSN: 1008973X     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (8)

1. AGRAWAL R, FALOUTSOS C, SWAMI A. Efficient similarity search in sequence database [A]. Proceedings of 4th International Conference on Foundations of Data Organization and Algorithm [C]. New York: Springer, 1993: 69-84.
2. CHAN K, FU W. Efficient time series matching by wavelets [A]. Proceedings of the 15th IEEE Inter national Conference on Data Engineering [C]. Sydney: IEEE, 1999: 126-133.
3. YOON J, LEE J, KIM S. Trend similarity and prediction in time-series databases [A]. Proceedings of SPIE on Data Mining and Knowledge Discovery: Theory, Tools, and Technology II [C]. Washington: SPIE, 2000: 201-212.
4. KEOGH E. Fast similarity search in the presence of longitudinal scaling in time series databases [A]. Proceedings of the 9th International Conference on Tools with Artificial Intelligence [C]. Newport Beach: IEEE, 1997: 578-584.
5. BAEZA-Yates R, NAVARRO G. A faster algorithm for approximate string matching [A]. Proceedings of CPM' 96 [C]. New York: Spirnger, 1996: 1-23.
6. BAEZA-YATES R, NAVARRO G. A practical index for text retrieval allowing errors [J]. CLEI, 1997, 1: 273-282.
7. GUO Si-yu WU Tie-jun. Fast algorithm for mining similar sub-trend sequence in time-series databases [J]. Journal of Zhejiang University: Engineering Science, 2002, 36(4): 421-426.
8. KEOGH E, KASETTY S. On the need for time series data mining benchmarks: A survey and empirical demonstration [A]. Proceedings of 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining [C]. Edmonton: ACM, 2002: 102-111.