Zipf's law (/ z ɪ f /; German pronunciation:) is an empirical law stating that when a list of measured values is sorted in decreasing order, the value of the n-th entry is often approximately inversely proportional to n. The best known instance of Zipf's law applies to the frequency table of words in a text or corpus of natural language:

齐夫定律 （英语：Zipf's law， IPA /ˈzɪf/ ）是由 哈佛大学 的 语言学家 乔治·金斯利·齐夫 （George Kingsley Zipf）于1949年发表的实验定律。 它可以表述为：在 自然语言 的 语料库 里，一个单词出现的频率与它在频率表里的排名成 反比 。

齐夫定律（英語： Zipf's law ，IPA： / ˈ z ɪ f / ）是由哈佛大學的語言學家 喬治·金斯利·齊夫 （ 英语 ： George Kingsley Zipf ） 于1949年发表的实验定律。 它可以表述为：在 自然语言 的 語料庫 裡，一个单词出现的频率与它在频率表里的排名成 反比 。

Jan 30, 2025 · 齐普夫定律（Zipf’s Law） 是一种经验法则，描述了 单词频率分布 在自然语言中的规律。 它指出，在一篇文本或一个语料库中，单词的出现频率 f f f 与其频率排名 r r r 之间存在如下关系：

Mar 21, 2024 · Zipf's law is an empirical formula discovered by George Zipf in 1930s. Zip's law describes the relationship between the frequency of words in language corpus and their rank in a frequency sorted list. In this article, we will be diving into the concept of Zipf’s law and its application in natural language processing.

Mar 9, 2025 · Zipf’s law, in probability, assertion that the frequencies f of certain events are inversely proportional to their rank r. The law was originally proposed by American linguist George Kingsley Zipf (1902–50) for the frequency of usage of …

In linguistics, the brevity law (also called Zipf's law of abbreviation) is a linguistic law that qualitatively states that the more frequently a word is used, the shorter that word tends to be, and vice versa; the less frequently a word is used, the longer it tends to be. [1]

Here, we present a general theoretical derivation of Zipf’s law, providing a synthesis and extension of previous approaches. First, we show that combining Gibrat’s law at all rm levels with random processes of rm’s births and deaths yield Zipf’s law under a “balance” condition between a rm’s growth and death rate.

Zipf's law, named after the Harvard linguistic professor George Kingsley Zipf (1902-1950), is the observation that frequency of occurrence of some event (P ), as a function of the rank (i) when the rank is determined by the above frequency of occurrence, is a power-law function P i ~ 1/i a with the exponent a close to unity (1).

This unexpectedly elegant distribution is called the Zipfian rank-size power law distribution where frequency is inversely proportional to rank with a coefficient of close to -1. This phenomenon has been further found in other types of data, including other language corpora, city populations (Auerbach 1913), corporation sizes, and income rankings.