Improving Recommender Systems Algorithms for Personalized Music Video Television by Incorporating User Consumption Behaviour and Multiple Types of User Feedback

This thesis explores the effects of incorporating user consumption behavior and multiple types of user feedback to improve recommender systems for personalized music video television. An industrial use case is made possible by the availability of anonymized user interaction data on curation-based personalized music television system provided by...