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Steam Recommendation System
May 03, 2023 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Samin Batra, Varun Sharma, Yurou Sun, Xinyao Wang, Yinyu Wang
arXiv ID
2305.04890
Category
cs.IR: Information Retrieval
Citations
1
Venue
arXiv.org
Last Checked
4 months ago
Abstract
We aim to leverage the interactions between users and items in the Steam community to build a game recommendation system that makes personalized suggestions to players in order to boost Steam's revenue as well as improve the users' gaming experience. The whole project is built on Apache Spark and deals with Big Data. The final output of the project is a recommendation system that gives a list of the top 5 items that the users will possibly like.6
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