one
METHODS AND SYSTEMS FOR GENERATING RECOMMENDATIONS FOR CONTACTING USERS THROUGH THE USE OF A CONTEXTUAL MULTI-ARMED BANDIT FRAMEWORK

Abstract:

Methods and systems are described for machine learning algorithms that dynamically allocate traffic to contact strategies that are performing well, while allocating less traffic to contact strategies that are underperforming. In particular, the methods and systems discussed are for the use of a contextual multi-armed bandit framework for applications that have both immediate results and long-term results, in which immediate results are correlated with the long-term results (e.g., results related to debt collection strategies).