Abstract
We study the problem of constructing a probabilistic rating system for team competitions. Unlike previous studies, we consider a setting where the competition can be broken down into relatively small individual tasks, and it is reasonable to assume that each task is done by a single team member. We begin with a simplistic naïve Bayes approach which is this case reduces to logistic regression and then develop it into a more complex model with latent variables trained by expectation–maximization. We show experimental results that validate our approach.
Keywords
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Acknowledgements
This research has been partially supported by the Russian Foundation for Basic Research grant no. 15-29-01173, Government of the Russian Federation grant 14.Z50.31.0030, and the Presidential Grant for Leading Scientific Schools, NSh-3856.2014.1. I also thank Alexey Tugarev for providing access to the database of “What? Where? When?” tournament results.
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Nikolenko, S. (2015). A Probabilistic Rating System for Team Competitions with Individual Contributions. In: Khachay, M., Konstantinova, N., Panchenko, A., Ignatov, D., Labunets, V. (eds) Analysis of Images, Social Networks and Texts. AIST 2015. Communications in Computer and Information Science, vol 542. Springer, Cham. https://doi.org/10.1007/978-3-319-26123-2_1
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DOI: https://doi.org/10.1007/978-3-319-26123-2_1
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