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Explaining Zipf's law via a mental lexicon

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成果类型：

期刊论文

作者：

Allahverdyan, Armen E.*;Deng, Weibing;Wang, Q. A.

通讯作者：

Allahverdyan, Armen E.

作者机构：

[Deng, Weibing; Wang, Q. A.; Allahverdyan, Armen E.] ISMANS, Lab Phys Stat & Syst Complexes, F-72000 Le Mans, France.

[Allahverdyan, Armen E.] Yerevan Phys Inst, Yerevan 375036, Armenia.

[Deng, Weibing; Wang, Q. A.] Univ Maine, UMR CNRS 6283, IMMM, F-72085 Le Mans, France.

[Deng, Weibing] Hua Zhong Normal Univ, Complex Sci Ctr, Wuhan 430079, Peoples R China.

[Deng, Weibing] Hua Zhong Normal Univ, Inst Particle Phys, Wuhan 430079, Peoples R China.

通讯机构：

[Allahverdyan, Armen E.] I

ISMANS, Lab Phys Stat & Syst Complexes, 44 Ave Bartholdi, F-72000 Le Mans, France.

语种：

英文

期刊：

Physical Review E

ISSN：

2470-0045

年：

2013

卷：

期：

页码：

062804

DOI：

10.1103/PhysRevE.88.062804

基金类别：

Region des Pays de la LoireRegion Pays de la Loire [2010-11967]; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [10975057, 10635020, 10647125, 10975062]; Programme of Introducing Talents of Discipline [B08033]; PHC CAI YUAN PEI Programme (LIU JIN OU) [6050, 2010008104]

机构署名：

本校为其他机构

院系归属：

物理科学与技术学院

摘要：

Zipf's law is the major regularity of statistical linguistics that has served as a prototype for rank-frequency relations and scaling laws in natural sciences. Here we show that Zipf's law—together with its applicability for a single text and its generalizations to high and low frequencies including hapax legomena—can be derived from assuming that the words are drawn into the text with random probabilities. Their a priori density relates, via the Bayesian statistics, ...

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