Module and Class to extract from a text.txt file the "n" most common words
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Updated
Mar 1, 2022 - Python
Module and Class to extract from a text.txt file the "n" most common words
Handy frequency lists from corpora and a few related utilities.
Twitter Engine using the phoenix framework in elixir for Distributed Operating system class
A tool for the visualization of word frequency differences.
Projects related to Computation Linguistics
TypeScript implementation of the Vsauce paperclip experiment.
A very simple example of dealing with text input
Dart implementation of a Zipf-distributed random number generator.
Analyzes texts for compliance with the second Zipf's and Heaps law.
Análisis de 'El Señor de los Anillos' mediante la Ley de Zipf: un estudio detallado de la distribución de frecuencias de palabras en la trilogía de Tolkien para explorar la aplicabilidad de esta fascinante ley estadística en la literatura épica.
Zipf's law has been proven on the Turkish and English versions of Harry Potter and the Philosopher's Stone.
Analysis using Natural Language Toolkit(NLTK), Numpy, Pandas and Matplotlib
It is a very different task, as here I am going to cluster 200 different texts related to games and sports in 2 or more different clusters. we can also use zipf plot to determine how many useful clusters can be formed.
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