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Movie Recommender

Movie Recommender is a simple Java based program that allows you to select movies from a huge dataset of over 5000 movies and display information about them. The program will recommend movies to you based of other movies and genres that you enjoy.

Info: The program was intended to use the SPARQL database as a bridge and process the algorithm in Python but we ran into tons of problems with using Java, SPARQL and Python together so we deiced it was best to remove the python component and translate it to Java.

How to use:

  • Clone or download this repository by running command below or click here
git clone https://github.com/EwyBoy/Movie-Recommender
  1. Open the project folder Movie Recommender as a project in IntelliJ (Have not tested Eclipse)
  2. Make sure the two required libraries found in the lib are recognized and added to your project settings. Both GSON.jarand the entire lib folder inside lib/apache-jena-3.11.0/
  3. Make sure language level is set to Java 8. Don't use any other version of Java.
  4. To start the program run public static void main(String[] args)
  5. The start window should appear:
  6. Click Start to launch the program. This can take a few seconds..
  7. The movie selection window will appear. Here you must select 5 movies from the list by double clicking on the entry in the list. You can also search the list by typing in the search bar above followed by pressing enter. To clear the search press backspace until search field is empty followed by pressing enter. You know a movie is selected when you can see the info about that movie on the display.
  8. To add a movie to the your list, select a movie and press the Add Movie To List button.
  9. If you make any mistakes you can clear the list by simply pressing the Reset List button.
  10. Press next to continue after selecting 5 movies you enjoy.
  11. This is the genre selection menu. Same rules apply here.
  12. Once you have selected 3 genres press next to get your movie recommendations.
  13. Her you can read about your recommendations.
  14. Enjoy!