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AJAX-Movie-Recommendation-System-with-Sentiment-Analysis
A content-based recommender system that recommends movies similar to the movie the user likes and analyses the sentiments of the reviews given by the user
#ajax#api#machine-learning#movie-recommendation#movie-recommendation-system#movie-recommender
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README preview
Content-Based-Movie-Recommender-System-with-sentiment-analysis-using-AJAX
Updated version of this application can be found at: https://github.com/kishan0725/The-Movie-Cinema
Content Based Recommender System recommends movies similar to the movie user likes and analyses the sentiments on the reviews given by the user for that movie.
The details of the movies(title, genre, runtime, rating, poster, etc) are fetched using an API by TMDB, https://www.themoviedb.org/documentation/api, and using the IMDB id of the movie in the API, I did web scraping to get the reviews given by the user in the IMDB site using beautifulsoup4 and performed sentiment analysis on those reviews.
Link to youtube demo: https://www.youtube.com/watch?v=dhVePtyECFw
The Movie Cinema
I've developed a similar application called "The Movie Cinema" which supports all language movies. But the only thing that differs from this application is that I've used the TMDB's recommendation engine in "The Movie Cinema". The recommendation part developed by me in this application doesn't support for multi-language movies as it consumes 200% of RAM (even after deploying it to Heroku) for generating Count Vectorizer matrix for all the 700,000+ movies in the TMDB.
Link to "The Movie Cinema" application: https://tmc.kishanlal.dev/
If you can't find the movie you're searching for through auto-suggestions while typing, there's no need to worry. Simply type the name of the movie and press "enter". Even if you make some typos, it should still work fine.
Source Code: https://github.com/kishan0725/The-Movie-Cinema
Featured in Krish's Live Session on YouTube
