Find the original paper here:
https://arxiv.org/pdf/1901.00521.pdf
Zipf' s Law is observed when words are inversely proportional to their frequency in a given text. Heap' s Law predicts how many unique words we expect to find in a random text sample. Neither of these laws are perfect because they are empirical.
We offer a new approach for studying type- token distribution.
This is a Summer of Math Expositions 2022 group entry.
Source code for Manim in this video: https://github.com/univalency/Manim-a...
(00:00) - What problem are we solving ?
(01:40) - Our method and approach
(02:26) - Uniform corpus
(03:37) - Apply our formula to cards
(04:17) - From recursion to explicit formula
(05:22) - Non- uniform corpus
(06:44) - Predict real text samples !
(11:09) - Demonstration with the Bible
#some2
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