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      <title>SIGFPAI2016</title>
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      <description>&lt;p&gt;In this paper, we propose a new similarity measure for time series data, that is called $k$-gram order preserving kernel. This kernel depends on the similarity of the shapes of data instead of that of the values. Moreover, we propose a new classification method using the kernel without adjusting the parameter $k$. Furthermore, we confirm the superiority of the proposed method by computer experiment.&lt;/p&gt;</description>
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