AI RESEARCH
Driving Engagement in Daily Fantasy Sports with a Scalable and Urgency-Aware Ranking Engine
arXiv CS.LG
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ArXi:2604.13796v1 Announce Type: cross In daily fantasy sports (DFS), match participation is highly time-sensitive. Users must act within a narrow window before a game begins, making match recommendation a time-critical task to prevent missed engagement and revenue loss. Existing recommender systems, typically designed for static item catalogs, are ill-equipped to handle the hard temporal deadlines inherent in these live events. To address this, we designed and deployed a recommendation engine using the Deep Interest Network (DIN) architecture.