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Analysing the Hierarchical Organization of Text by Using Biologically-Inspired Statistical Methods

机译:使用生物学启发的统计方法分析文本的层次结构

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摘要

We have binarily encoded written monologues in a similar manner to the encoding of a continuous electrical signal of neuronal networks. The encoding keys have been carefully designed to include phrases that are co-referents. Only such keys produce binary series, which have an hierarchical fractal structure. This fractal structure can be revealed by using a statistical tool named “Fano factor”. By outlining the analogy between the hierarchical structure of neuronal electrical activity and the hierarchical structure of text, we try to link the organization of text and neuronal activity.
机译:我们已经以类似于对神经网络的连续电信号进行编码的方式对书面独白进行了二进制编码。编码关键字经过精心设计,以包含作为共同指称的短语。只有这样的密钥才能生成具有分级分形结构的二进制序列。通过使用名为“ Fano factor”的统计工具可以揭示这种分形结构。通过概述神经元电活动的层次结构与文本的层次结构之间的类比,我们尝试将文本的组织与神经元活动联系起来。

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  • 来源
    《Journal of Quantitative Linguistics》 |2008年第4期|318-339|共22页
  • 作者

    Israela Becker; Eli Flaxer;

  • 作者单位

    AFEKA - Tel-Aviv Academic College of Engineering, Tel-Aviv, Israel;

    AFEKA - Tel-Aviv Academic College of Engineering, Tel-Aviv, Israel|School of Chemistry, The Raymond and Beverly Sackler Faculty of Exact Sciences, Tel-Aviv University, Tel-Aviv, Israel;

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