A comparison of two fluctuation analyses for natural language clustering phenomena: Taylor vs. ebeling& neiman methods.
A comparison of two fluctuation analyses for natural language clustering phenomena: Taylor vs. ebeling& neiman methods.
复制标题
自然语言聚类现象的两种波动分析的比较：Taylor 与 ebeling
DOI：
10.1142/s0218348x2150033x
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发表时间：
2021
期刊：
影响因子：
4.7
通讯作者：
Kumiko Tanaka-Ishii and Shuntaro Takahashi
中科院分区：
文献类型：
--
作者：
野元 貴史;田畑 智志;渡辺 義浩;中谷英明;Kumiko Tanaka-Ishii and Shuntaro Takahashi
This paper considers the fluctuation analysis methods of Taylor and Ebeling & Neiman. While both have been applied to various phenomena in the statistical mechanics domain, their similarities and differences have not been clarified. After considering their analytical aspects, this paper presents a large-scale application of these methods to text. It is found that both methods can distinguish real text from independently and identically distributed (i.i.d.) sequences. Furthermore, it is found that the Taylor exponents acquired from words can roughly distinguish text categories; this is also the case for Ebeling and Neiman exponents, but to a lesser extent. Additionally, both methods show some possibility of capturing script kinds.
