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Movie Recommendation Engine based on a K-Means clustering algorithm of IMDB public data. Node server for user interface.

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Codejam-2016 Senior Challenge

Team: Pouteam -- Senior_Team20

Using the app

The folder Node Server contains a Node JS server that hosts our website.

Instructions to install and run the server are in the folder's readme.

The website will ask for a name, a few genres and some tv shows that the user watched and liked. It will then recommend new TV Shows to watch based on a recommendation algorithm.

Users are saved by name and if a user comes back to the website he will get recommendations directly with the possibility of changing his genre choices / liked tv shows choices.

Recommendation Algorithm

The folder Algo contains our recommendation algorithm.

Language used: Python

Machine Learning Libraries used: scikit-learn, NumPy, SciPy

Data Fetching

The folder Data Fetcher contains Python code to get our data.

We fetched data from IMDB and MetaCritic

UI design

Sketches were made with pen and paper (dropped in the ECSESS lounge).

We looked for a very simple and minimalistic design as it is functionnal and easy to do in a limited time frame.

We choosed to implement the application as a website because it seemed like the go-to way of displaying our desired UI.

The final result is slightly different to the sketches due to some tweaking.

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Movie Recommendation Engine based on a K-Means clustering algorithm of IMDB public data. Node server for user interface.

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