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Behavioral Player Rating in Competitive Online Shooter Games
Competitive online games use rating systems for matchmaking; progression-based algorithms that estimate the skill level of players with interpretable ratings in terms of the outcome of the games they played.
Player Modeling using Behavioral Signals in Competitive Online Games
We then use the created models to predict ranks for different groups of players in the data.
How does the User's Knowledge of the Recommender Influence their Behavior?
Recommender systems have become a ubiquitous part of modern web applications.
Evaluating Team Skill Aggregation in Online Competitive Games
Rating systems leverage statistical estimation to rate players' skills and use skill ratings to predict rank before matching players.
The Evaluation of Rating Systems in Team-based Battle Royale Games
It alleviated most of the challenges faced by the other metrics while adding the freedom to adjust the focus of the evaluations on different groups of players.
The Evaluation of Rating Systems in Online Free-for-All Games
However, less attention has been given to the evaluation metrics of these systems.
Investigating Potential Factors Associated with Gender Discrimination in Collaborative Recommender Systems
The proliferation of personalized recommendation technologies has raised concerns about discrepancies in their recommendation performance across different genders, age groups, and racial or ethnic populations.
