Statistical models for time sequences data mining

IEEE/IAFE Conference on Computational Intelligence for Financial Engineering, Proceedings (CIFEr)

Volumn 2003-January, Issue , 2003, Pages 347-354

  Ting, J K ^a   Ng, M K ^a   Rong, Hongqiang ^a   Huang, J Z ^a  

^a UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Clustering algorithms; Credit cards; Data mining; Delay effects; DNA; Mathematical model; Mathematics; Mobile handsets; Predictive models; Sequences

Indexed keywords

ARTIFICIAL INTELLIGENCE; BIOINFORMATICS; DATA MINING; DNA; DNA SEQUENCES; FORECASTING; MATHEMATICAL MODELS; MATHEMATICAL TECHNIQUES; REGRESSION ANALYSIS;

CREDIT CARDS; DELAY EFFECTS; MOBILE HANDSETS; PREDICTIVE MODELS; SEQUENCES;

CLUSTERING ALGORITHMS;

EID: 9744267260     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CIFER.2003.1196281     Document Type: Conference Paper

References (7)

1. R. Agrawal, C. Faloutsos, and A. Swami, Efficient Similarity Search in Sequence Databases, Foundations of Data Organizations and Algorithms (FODO) Conference, 1993.
2. R. 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, Proceedings of the 21st VLDB Conference, 1995.
3. C. Faloutsos, M. Ranganathan and Y. Manolopoulos, Fast subsequence matching in time-series databases, Proceedings of ACM SIGMOD Conference, 1994.
4. M. K. Ng, and J. Z. Huang, Data-mining massive time series astronomical data: challenges, problems and solutions, Information and Software Technology 41 (1999) 545-556.
5. D. Rafiei, and A. Mendelzon, Similarity-based Queries for Time Series Data, Proceedings of ACM SIGMOD Conference, ACM, 1997.
6. J. K. Ting, Time Sequences Data Mining, MPhil thesis, The University of Hong Kong, 2001.
7. K. H. Skinner, Temporal Data Mining Techniques for Classification of Time Series Data, BSc thesis, Australian National University, 1997.