Time Sequence Clustering Based on Edit Distance

Hai Yan Zhou; Jing Song Shan

doi:10.4028/www.scientific.net/AMM.401-403.1428

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 401-403Time Sequence Clustering Based on Edit Distance

Time Sequence Clustering Based on Edit Distance

Abstract:

A time sequence clustering algorithm based on edit distance is proposed in the paper, which solves the problem that the existing clustering algorithms for time sequence data is inefficient because of ignorance of different time span of time sequence data. Firstly, the algorithm calculates the distance between time sequences on which a distance matrix is determined. In the second place, for a given time sequence set, a forest with n binary trees is established in terms of the distance matrix and then merge the trees. Finally, a cluster clustering algorithm is called to dynamically adjust the clustering results, and then real-time clustering structure is obtained. Experimental results demonstrated that the algorithm has higher efficiency and clustering quality.

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Periodical:

Applied Mechanics and Materials (Volumes 401-403)

Pages:

1428-1431

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.401-403.1428

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Online since:

September 2013

Authors:

Hai Yan Zhou, Jing Song Shan

Keywords:

Clustering Algorithm, Edit Distance, Time Sequence

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