Please use this identifier to cite or link to this item:
http://hdl.handle.net/10071/23677
Author(s): | Bunga, R. Batista, F. Ribeiro, R. |
Editor: | Cucchiara, R., Fred, A., & Filipe, J. |
Date: | 2021 |
Title: | From implicit preferences to ratings: Video games recommendation based on collaborative filtering |
Volume: | 1 |
Pages: | 209 - 216 |
Event title: | 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KDIR |
ISSN: | 2184-3228 |
ISBN: | 978-989-758-533-3 |
DOI (Digital Object Identifier): | 10.5220/0010655900003064 |
Keywords: | 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. |
Peerreviewed: | yes |
Access type: | Open Access |
Appears in Collections: | CTI-CRI - Comunicações a conferências internacionais |
Files in This Item:
File | Description | Size | Format | |
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conferenceobject_82722.pdf | Versão Aceite | 224,33 kB | Adobe PDF | View/Open |
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