wangjiajia95/movie-recommender-java-spring-boot-react-js

MovieRecommender

Overview

This is a 3 week long capstone project after study at Ada. Project goals included learning new tech stack, framework, combine with my personal interest -- recommender engine, and implement them in a short period of time.

MovieRecommender is a personalized recommendation engine based on MovieDB and Twitflicks resources. Users can search or retrieve movie resources, and submit their own ratings on each movie, they can then get recommended based on ratings of a list of Movies they rated by content based algorithm.

Tools and Technologies

Front-end: ReactJS

Back-end: JAVA Spring Boot

Dependency: Spring Data JPA, Spring Batch, Spring Boot DevTools, Spring Web, HSQLDB

Build: Apache Maven, Jar file

Recommendation: A content-based algorithm implemented in Java

Deployment: AWS Elastic Beanstalk

Main Features

• Users can get movies and grouped by upcoming/countries/genres/years/top reviews.

• Users can rate a movie and check it later on their rating page.

• I explored multiple recommendation algorithms such as content based recommender, collaborative filtering recommender, etc. In my project, Users will get recommendation based on a list of movies they rated by content based algorithm.