https://github.com/play3rzer0/wordcount

Using NLP To Find Most Common Words In Text Documents
https://github.com/play3rzer0/wordcount

natural-language-processing nlp nltk-python python text-processing

Last synced: about 4 hours ago
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Using NLP To Find Most Common Words In Text Documents

• Host: GitHub
• URL: https://github.com/play3rzer0/wordcount
• Owner: Play3rZer0
• Created: 2019-03-10T23:01:43.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2019-03-15T21:11:43.000Z (over 5 years ago)
• Last Synced: 2024-07-11T14:25:42.054Z (4 months ago)
• Topics: natural-language-processing, nlp, nltk-python, python, text-processing
• Language: Python
• Size: 6.84 KB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# WordCount

Using NLP To Find Most Common Words In Text Documents.

Process the frequency or number of times the most common words in a text document occurs. This makes use of the NLTK

(Natural Language Toolkit) 3.0 in a Python 2.7.1x or 3.x environment. I was originally using Python version 2.7.10 as a virtual environment within a Python 3.6.5 Anaconda version. The code was originally in 2.7.10, but it was modified to 

support the latest version.

The following modules must be imported:

- collections

- re

- nltk

The stopwords must also be imported from nltk.corpus.

The ff. is the synatx to run the code from a terminal command prompt (Linux, MacOS, Unix) or command prompt (Windows):

python .py