uxioandrade/Anime-Recommendation-Engine

A full-stack Anime Recommendation Engine App built with Scala, React, PostgreSQL and Spark

Anime Recommendation Engine

The purpose of this project is to implement different recommendation algorithms and integrate them in a web app.

Short Demo

Version Summary

• Play Framework: 2.7.2
• React: 16.8.6
• Create React App: 2.1.8
• Spark: 2.4.0
• PostgreSQL: 9.4
• Python 3.X

Setting up

Prerequisites

• Node.js
• scala
• Docker

Getting started

First, you need to navigate to the following datasets:

• dataset And download the files anime_cleaned.csv,animelists_cleaned and users_cleaned
• Save the datasets in a directory named datasets in the root directory
• Now run the scripts dataset_cleaner.py and then clean_images.py using python3
• Execute the init_db_docker.sh file. Uncomment the first lines if you don't have the necessary docker images
• At this point, you can execute sbt run, which will trigger npm run start
• Finally, enter the sbt console and run util.RecommendationModel, which will save the ALS model.

License

This software is licensed under the MIT license