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SteamMatcher

Recommender system

python pandas ML
Table of Contents

Introduction

This is a college project I did alongside my wonderful classmates.

The model recommends games from Steam, an online video game store. It applies a collaborative filtering technique based on building graphs with relationships between games using community data and then suggest titles similar to those in a player’s profile.

The source code is not hosted public. Contact me if you want access.

Web Interface

There is a web interface at the root (/) that allows the user to interact with the model.

This is the first screen the user sees. It lets the user enter a Steam user ID to search.

main menu

Error menu

This screen appears if an error occurs while fetching the user’s information, for example if the profile is private or the ID is invalid.

error menu

Recommendations menu

This screen shows the 20 recommendations returned for the user. It includes the game cover, its price, the most relevant user tags, and a short description. By clicking the images, you can go directly to the game’s store page on Steam.

recommendations menu

REST API

There is an API endpoint that returns a JSON file containing the top 20 recommendations for a given user.

Endpoint

GET /recommendation/json

Co-Authors

  • Daniel Pantoja Joaristi
  • Jorge Hernández Palop
  • Marco Casteleiro Trigueros
  • Álvaro Arbona Rodríguez
  • Óscar Marín Esteban