CEU Electronic Theses and Dissertations, 2021
| Author | Kiss, Gyula |
|---|---|
| Title | Product Recommender Systems in Sports Betting |
| Summary | Personalized recommenders are apparent to anyone using web stores like Amazon or content providers like Netflix today. Based on implicit activity of users purchasing or watching products or explicitly rating items these e-commerce sites offer recommendations for other products to consider and help users to choose products from a large set. The idea is to predict the individual user’s interest based on preferences and activities of many users. Sports betting can be considered as selling bets to the players on various sport events. The product line in sports betting is very large, not just because of the abundance of sport events, but the various forms of bets (industry term is market), e.g. for a single football match players can bet on the winning team, number of goals, half time result, and dozens more. The significance of the project is to explore and investigate the machine learning methods and algorithms of recommenders and their adaptation to the Sports Betting industry, experimenting with real production data. |
| Supervisor | Gyorgy Bogel |
| Department | Economics MSc |
| Full text | https://www.etd.ceu.edu/2021/kiss_gyula.pdf |
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