Modeling User Dynamics for Item Recommendation

Users may show a behavioral pattern in consuming the items. For example, one might assume that a user is interested in comedy movies when this user watches comedy movies frequently. Recommender systems are designed to understand the preference of a user from his interactions with the items and suggest items that correspond to his preference....

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...