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Time series data mining can be treated as an sub set of data mining and it is important in the fields of economics, medical science, manufacturing segments, space technology etc. In this paper, the authors propose a new method for the pattern visualization. The multiple time-series problem of modeling and predicting simultaneous movements of a collection of time-sensitive variables that are related to each other has received much less attention. The visualization technique they proposed is basically converts a physical action to a set of time variable sequential data. The key challenge is how to capture the multiple time series data simultaneously.
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