text_mining_project

Purpose

This project analyse text generated from customer reviews on hotels around Europe.

The different text mining techniques used include:

Document Classification
- Logtistic Regression
- XGBoost
- Random Forest
- Naïve Bayes
Sentiment Analysis
- Vader Sentiment
Topic Modelling
- LDA
  - Mallet
  - Gensim

Name		Name	Last commit message	Last commit date
Latest commit History 5 Commits
.ipynb_checkpoints		.ipynb_checkpoints
.vscode		.vscode
Classification		Classification
Pre-processing		Pre-processing
Topic Modelling		Topic Modelling
flask_backend		flask_backend
frontend		frontend
images		images
.gitattributes		.gitattributes
.gitignore		.gitignore
Document Summarisation (Future work).ipynb		Document Summarisation (Future work).ipynb
G2T6_FinalReport.pdf		G2T6_FinalReport.pdf
README.md		README.md
frequency_bigramdictionary_en_243_342.txt		frequency_bigramdictionary_en_243_342.txt
frequency_dictionary_en_82_765.txt		frequency_dictionary_en_82_765.txt
unseen_data.csv		unseen_data.csv