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Authors: Rosária Bunga 1 ; Fernando Batista 2 ; 1 and Ricardo Ribeiro 2 ; 1

Affiliations: 1 ISCTE - Instituto Universitário de Lisboa, Av. das Forças Armadas, Portugal ; 2 INESC-ID Lisboa, Portugal

Keyword(s): Recommendation System, Collaborative Filtering, Implicit Feedback.

Abstract: This work studies and compares the performance of collaborative filtering algorithms, with the intent of proposing a videogame-oriented recommendation system. This system uses information from the video game platform Steam, which contains information about the game usage, corresponding to the implicit feedback that was later transformed into explicit feedback. These algorithms were implemented using the Surprise library, that allows to create and evaluate recommender systems that deal with explicit data. The algorithms are evaluated and compared with each other using metrics such as RSME, MAE, Precision@k, Recall@k and F1@k. We have concluded that computationally low demanding approaches can still obtain suitable results.

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Paper citation in several formats:
Bunga, R.; Batista, F. and Ribeiro, R. (2021). From Implicit Preferences to Ratings: Video Games Recommendation based on Collaborative Filtering. In Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2021) - KDIR; ISBN 978-989-758-533-3; ISSN 2184-3228, SciTePress, pages 209-216. DOI: 10.5220/0010655900003064

@conference{kdir21,
author={Rosária Bunga. and Fernando Batista. and Ricardo Ribeiro.},
title={From Implicit Preferences to Ratings: Video Games Recommendation based on Collaborative Filtering},
booktitle={Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2021) - KDIR},
year={2021},
pages={209-216},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010655900003064},
isbn={978-989-758-533-3},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2021) - KDIR
TI - From Implicit Preferences to Ratings: Video Games Recommendation based on Collaborative Filtering
SN - 978-989-758-533-3
IS - 2184-3228
AU - Bunga, R.
AU - Batista, F.
AU - Ribeiro, R.
PY - 2021
SP - 209
EP - 216
DO - 10.5220/0010655900003064
PB - SciTePress

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