Abstract
Zipf’s law – or Estoup-Zipf’s law – is an empirical fact of computational linguistics which relates rank and frequency of words in natural languages. The law suggests modelling by distributions of “hyperbolic type”,. We present a satisfactory general definition and an information theoretical characterization of the resulting hyperbolic distributions. When applied to linguistics this leads to a property of stability and flexibility, explaining that a language can develop towards higher and higher expressive powers without changing its basic structure.
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Harremoës, P., Topsoe, F. (2006). Zipf’s Law, Hyperbolic Distributions and Entropy Loss. In: Ahlswede, R., et al. General Theory of Information Transfer and Combinatorics. Lecture Notes in Computer Science, vol 4123. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11889342_50
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DOI: https://doi.org/10.1007/11889342_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46244-6
Online ISBN: 978-3-540-46245-3
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