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Rights Holder and Contact
Choi, Brian; Ryu, MiSun; Panchal, Dharmesh; Le, Andrew
Description
MAS DSE Group 4 Capstone project: Building Recommender Systems for Video Games on Steam The goal of this project was to build a recommender system for video games on Steam. We used the Bayesian Personalized Ranking algorithm on game ownership data to construct a model that would recommend games for users to buy. On top of that, we focused on a variety of data analysis tasks to look at how well the model atacks the cold start problem and how well genre classification corresponds with user purchase patterns. Research Data Curation Program, UC San Diego, La Jolla, 92093-0175 (https://lib.ucsd.edu/rdcp) Choi, Brian; Ryu, MiSun; Panchal, Dharmesh; Le, Andrew (2019). Building Recommender Systems for Video Games on Steam. In Data Science & Engineering Master of Advanced Study (DSE MAS) Capstone Projects. UC San Diego Library Digital Collections. https://doi.org/10.6075/J0FQ9TZM
Type
dataset
Identifier
ark:/20775/bb5021836n
Subject
Bayesian Personalized Ranking (BPR) Collaborative filtering Video games Data Science & Engineering Master of Advanced Study (DSE MAS) Steam Capstone projects LightFM (Python package) Recommender system DSE MAS - 2019 Cohort
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