Sentiment Analysis movies and Recommandation System

Table of Contents

1. Project Overview
2. Technologies Used
3. Steps
4. Report and presentation
5. Conclusion
6. Contacts

1. Project Overview

The project is based on developing a versatile system that combines sentiment analysis and recommendation, with a user-friendly interface. The main objective is to enable users to explore and benefit from a personalized contextual experience. In this context, sentiment analysis aims to evaluate user comments on films, classifying them into categories such as positive, negative, or neutral. This evaluation feeds into a recommendation system that suggests films based on users' sentimental preferences. The user interface provides an intuitive platform to interact with these features.

2. Technologies Used

• scrapy
• BeautifulSoup
• Python
• Jupyter notebook
• NumPy
• Pandas
• Scikit-learn
• Flask
• HTML, CSS, JavaScript(for web application)

4. Report and presentation

you will find all details of project and architecutre in my report and presentation in the folder report and presentation good lecture .

• for link of report :

https://www.canva.com/design/DAFzGHHBKTg/BsXVKfx1JsvTAqWG121Zrw/edit?utm_content=DAFzGHHBKTg&utm_campaign=designshare&utm_medium=link2&utm_source=sharebutton

• for link of presentation :

https://www.canva.com/design/DAFzTrfN3oI/1I28ITtDsgc5d_q3R4JJtw/edit?utm_content=DAFzTrfN3oI&utm_campaign=designshare&utm_medium=link2&utm_source=sharebutton

5. Conclusion

In conclusion, our project has succeeded in creating an accurate sentiment analysis model and an efficient movie recommendation system based on similarity.

6. Contacts

For any information, suggestions, or questions, please contact me:

Name: Fannich Salma
Email: salma.fannich123@gmail.com
LinkedIn: Salma Fannich