https://github.com/0xkibh/simple-nlp

A simple NLP clustering program to cluster the text using TF-IDF and Word2Vec as feature extraction and K-Means Clustering as an algorithm
https://github.com/0xkibh/simple-nlp

gensim kmeans-clustering nlp pandas python tfidf word2vec

Last synced: 5 months ago
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A simple NLP clustering program to cluster the text using TF-IDF and Word2Vec as feature extraction and K-Means Clustering as an algorithm

• Host: GitHub
• URL: https://github.com/0xkibh/simple-nlp
• Owner: 0xkibh
• Created: 2022-11-09T16:04:02.000Z (about 3 years ago)
• Default Branch: master
• Last Pushed: 2022-11-10T15:50:52.000Z (about 3 years ago)
• Last Synced: 2025-03-28T18:51:16.990Z (9 months ago)
• Topics: gensim, kmeans-clustering, nlp, pandas, python, tfidf, word2vec
• Language: Jupyter Notebook
• Homepage:
• Size: 31.3 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: Readme.md

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README

          
# Simple NLP Application

## Simple TF-IDF and K-Means Clustering

- This is a program to cluster the text on the basis of the word data.

- Text Preprocessing is done using basic python code

- Feature Extraction is done using TF-IDF algorithm

- And Clustering is done my K means clustering

## Simple Word2Vec and K-Means Clustering

- This is the code to cluster text similar to other one

- Here we used word2vec inplace of TF-IDF to extract the feature in vector

- Considering the limitation of TF-IDF(or BoW), word2vec seems better option

- And clustering is done same as above using KMeans