Flixr: Movie Recommendation System

Flixr aims to help its users make better choices about the movies that they watch on popular streaming services, regardless of the streaming service to which the movie may belong.

The goal of this application is to improve movie recommendations to our users, while also gaining insights into customer behavior.

For more details please refer to the project's design document.

Authors

Fangzhou Guo

Thomas Thompson

Vraj Desai

Zion Whitehall

Setting up the Project

API Service & Recommendation Engine Setup

Use any Java IDE, we suggest using IntelliJ:

• Download Java JDK 8. You can use this website

• Download IntelliJ Community Edition

• IntelliJ should automatically build the dependencies using Maven and the pom.xml file.

• Then, open MySQL workbench and run the queries included in the database folder.

• Please note that the com.flixr.configuration.ApplicationConstants class will need to have its MySQL credentials updated to match your environment.

Frontend Setup

Ensure you have NodeJS installed:

• Download NodeJS if needed.

Within the command line, perform the following actions:

• Navigate to the frontend project folder cs684-flixr/frontend

• Run npm install to download your dependencies

Running the Application

You will need to run both webservices to use the web application.

Run the Java API:

Within your IDE:

• Navigate to com.flixr.Application and click the public static void main() method.

• Click the green play button in IntelliJ to run the project.

• The API will be running GET and POST requests on localhost:3001

Run the NodeJS Frontend:

Within your commmand line:

• Navigate to the frontend project folder cs684-flixr/frontend

• Open up to localhost:3000 in your browser to see the webapp in action.

References

https://github.com/spring-guides/tut-react-and-spring-data-rest/tree/master/basic

http://girlincomputerscience.blogspot.com/search/label/Recommender%20Systems