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Web of Proceedings - Francis Academic Press
Web of Proceedings - Francis Academic Press

A Presentation of Time Series Algorithm Based on K-Mean and Its Application in Clustering

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DOI: 10.25236/isrme.2019.068


Yeping Peng

Corresponding Author

Yeping Peng


As the data volume of a time series database is much greater than that of an ordinary database, some general data mining tools cannot be applied to time series directly to generate satisfactory result. Therefore, a piecewise linearization representation algorithm is proposed for time series in this paper, which can greatly improve the computation speed of similarity measurement. Based on the piecewise linearization representation, a similarity calculation method is proposed, which is insensitive to various deformation of time series. The k-mean clustering algorithm is applied to time series represented by piecewise linearization for a desired result.


Time series, Algorithm, Similarity, K-mean, Clustering