Creating serendipity (i.e. “pleasant surprises for users”) is a primary goal of intelligent recommender systems. This project proposes an interdisciplinary approach to enhance the serendipity of TV recommendations that combines complementary knowledge from three disciplines – Computer Science, Language & Cognition and Communication Science.
The project examines the “back-end” or algorithms behind serendipitous TV recommendations (Computer Science), the “front-end” or the actual display of these recommendations (Language & Cognition), and the “effect” on users’ perceptions and satisfaction (Communication Science).
Stay tuned at: @SirupProject, #sirup-project