Ordinal analysis of lexical patterns.
暂无分享,去创建一个
[1] H. V. Ribeiro,et al. Permutation Jensen-Shannon distance: A versatile and fast symbolic tool for complex time-series analysis. , 2022, Physical review. E.
[2] M. Zanin,et al. Ordinal patterns-based methodologies for distinguishing chaos from noise in discrete time series , 2021, Communications Physics.
[3] Matjaž Perc,et al. History of art paintings through the lens of entropy and complexity , 2018, Proceedings of the National Academy of Sciences.
[4] A. Mehri,et al. Variation of Zipf's exponent in one hundred live languages: A study of the Holy Bible translations , 2017 .
[5] Armin Bunde,et al. Long-Range Memory in Literary Texts: On the Universal Clustering of the Rare Words , 2016, PloS one.
[6] Mark Steedman,et al. A massively parallel corpus: the Bible in 100 languages , 2014, Lang. Resour. Evaluation.
[7] Gemma Boleda,et al. Zipf’s Law for Word Frequencies: Word Forms versus Lemmas in Long Texts , 2014, PloS one.
[8] S. Piantadosi. Zipf’s word frequency law in natural language: A critical review and future directions , 2014, Psychonomic Bulletin & Review.
[9] Slav Petrov,et al. Syntactic Annotations for the Google Books NGram Corpus , 2012, ACL.
[10] Eduardo G. Altmann,et al. On the origin of long-range correlations in texts , 2012, Proceedings of the National Academy of Sciences.
[11] M. Montemurro,et al. Universal Entropy of Word Ordering Across Linguistic Families , 2011, PloS one.
[12] Stuart James,et al. The Cambridge Encyclopedia of Language (3rd ed.) , 2011 .
[13] Erez Lieberman Aiden,et al. Quantitative Analysis of Culture Using Millions of Digitized Books , 2010, Science.
[14] Wiebke Wagner,et al. Steven Bird, Ewan Klein and Edward Loper: Natural Language Processing with Python, Analyzing Text with the Natural Language Toolkit , 2010, Lang. Resour. Evaluation.
[15] Philip Hanna,et al. Extending Zipf’s law to n-grams for large corpora , 2009, Artificial Intelligence Review.
[16] O. Rosso,et al. Shakespeare and other English Renaissance authors as characterized by Information Theory complexity quantifiers , 2009 .
[17] Jack Grieve,et al. Quantitative Authorship Attribution: An Evaluation of Techniques , 2007, Lit. Linguistic Comput..
[18] J-P Eckmann,et al. Hierarchical structures induce long-range dynamical correlations in written texts. , 2006, Proceedings of the National Academy of Sciences of the United States of America.
[19] Ricard V. Solé,et al. Least effort and the origins of scaling in human language , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[20] Noam Chomsky,et al. The faculty of language: what is it, who has it, and how did it evolve? , 2002, Science.
[21] B. Pompe,et al. Permutation entropy: a natural complexity measure for time series. , 2002, Physical review letters.
[22] Marcelo A. Montemurro,et al. Long-range fractal correlations in literary corpora , 2002, ArXiv.
[23] W. Ebeling,et al. Entropy and Long-Range Correlations in Literary English , 1993, chao-dyn/9309005.
[24] Joseph H. Greenberg,et al. Some Universals of Grammar with Particular Reference to the Order of Meaningful Elements , 1990, On Language.
[25] W. Greg. The Concise Cambridge History of English Literature , 1943 .
[26] C. Lacor,et al. Chaos , 1876, Molecular Vibrations.
[27] David Crystal,et al. The Cambridge Encyclopedia of Language , 2012, Modern Language Review.
[28] W. Ditto,et al. Chaos: From Theory to Applications , 1992 .
[29] Claude E. Shannon,et al. Prediction and Entropy of Printed English , 1951 .
[30] G. Āllport. The Psycho-Biology of Language. , 1936 .
[31] G. Sampson. The Concise Cambridge History of English Literature , 2022 .