![]() ![]() Zipf originally developed his law in response to the observation that the frequency of words was inversely proportional to the rank of each word.įor example, the most common 20 words in English are listed in the following table. Artificial intelligence (in particular, "chat bots" that can chat with humans) relies on the limited number of questions and statements that people actually write in chats.Wealth distribution (a small number of people have large amounts of money, large numbers of people have small amounts of money).City populations (a small number of large cities, a larger number of smaller cities).As the basis of most approaches to image compression. ![]() Zipf Distributions occur naturally in many situations, for example in: Likewise, the 3rd most common word occurs about `1/3` as often as the most common word. In other words, the second most commonly used word occurs about `1/2` as often as the most common word. In general, the word with rank k has a frequency roughly proportional to `1/k`. The Zipf Distribution is an observation comparing rank and frequency of word occurrences. That relationship was observed by George Kingsley Zipf in the first half of the 20th century. It turns out that there is a relationship between the rank of a word's occurrence and the frequency of its use. Application 2: Zipf DistributionsĬonsider the most common words in English. Graph of `y=100(0.82)^t` on semilogarithmic axes. ![]()
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