Cognitive Recommender Systems

Traditionally, Recommender Systems have been recognized as playlist generators for video/music services (e.g., Netflix and Spotify), ecommerce product recommenders (e.g., Amazon and eBay), or social content recommenders (e.g., Facebook and Twitter). However, Recommender Systems in modern enterprises are highly data-driven and rely on users' cognitive aspects such as personality, behavior, and attitude. This project aims to introduce a new type of (data-driven, knowledge-driven and cognition-driven) intelligent recommender systems, namely Cognitive Recommender Systems, that will be able to understand the user’s preferences, predict user’s unknown favourites, and explore the adaptive mechanisms to enable intelligent actions within the compound and changing environments.