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Symbol Extraction Method and Symbolic Distance for Analysing Medical Time Series

机译:用于分析医学时间序列的符号提取方法和符号距离

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摘要

The analysis of time series databases is very important in the area of medicine. Most of the approaches that address this problem are based on numerical algorithms that calculate distances, clusters, index trees, etc. However, a symbolic rather than numerical analysis is sometimes needed to search for the characteristics of the time series. Symbolic information helps users to efficiently analyse and compare time series in the same or in a similar way as a domain expert would. This paper focuses on the process of transforming numerical time series into a symbolic domain and on the definition of both this domain and a distance for comparing symbolic temporal sequences. The work is applied to the isokinetics domain within an application called I4.
机译:时间序列数据库的分析在医学领域非常重要。解决该问题的大多数方法都是基于计算距离,聚类,索引树等的数值算法。但是,有时需要符号分析而不是数值分析来搜索时间序列的特征。符号信息可以帮助用户以与领域专家相同或相似的方式有效地分析和比较时间序列。本文着重于将数字时间序列转换为符号域的过程,以及该域的定义以及用于比较符号时间序列的距离。这项工作应用于名为I4的应用程序中的等速运动领域。

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