steam

A recommendation system for Steam using matrix factorization

Variables

int user_id: numerical ID to identify while anonymizing Steam users
str game_title: name of the game with which the user made an interaction
str behavior: type of behavior exhibited by user; can only be either "purchase" or "play"
int value: if the behavior value is "purchase", the value is always 1; otherwise, it specifies the number of hours the game has been played by the user

Files

Aside from README.md, the repository contains 2 other files:

1. steam-200k.csv, which contains the data used for training the recommendation system
2. steam.ipynb, which contains the code for training the recommendation system and recommending video games to a certain user

Remarks

This recommendation system was developed with the goal of exploring Tensorflow through making projects. In the future I hope to improve it by programming a more sophisticated model with three stages: retrieval, ranking, and post-ranking.

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Code authorship

2021 © Jessan Rendell G. Belenzo

Terms of use

Licensed under the GNU General Public License v3.0. See LICENSE.

Acknowledgments

The Tamber Team (2017). Steam Video Games, version 3. Retrieved October 29, 2021 from https://www.kaggle.com/tamber/steam-video-games.