A novel two-level clustering method for time series data analysis

Author:

Lai Cheng-Ping,Chung Pau-Choo,Tseng Vincent S.

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference25 articles.

1. Banerjee, A., & Ghosh, J. (2001). Clickstream clustering using weighted longest common subsequences. In Workshop on web mining of the first SIAM international conference on data mining, Chicago, USA.

2. Ben-Dor, A., & Yakhini, Z. (1998). Clustering gene expression pattern. Technique report of Hewlett-Packard Laboratories Israel HPL-98-190.

3. Berndt, D. J., & Clifford, J. (1994). Using dynamic time warping to find patterns in time series (pp. 359–370). Working notes of the knowledge discovery in databases workshop, Washington, USA.

4. Algorithm for clustering continuous density HMM by recognition error;Dermatas;IEEE Transactions on Speech and Audio Processing,1996

5. Duan, G., Suzuki, Y., & Kawagoe, K. (2006). Grid representation of time series data for similarity search. In Proceedings of the 22nd international conference on data engineering workshops (ICDEW’06) (p. x123).

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