Context Suggestion: Solutions and Challenges

Recommender systems (RS) have been popular for decades and many novel types of RS have been proposed and developed, such as context-aware recommender systems (CARS) which additionally take contexts (e.g., time, location, occasion, etc) into consideration to further assist users' decision makings. Meantime, the emergence of CARS also brings new recommendation opportunities, such as context suggestion which recommends a list of appropriate contextual situations for the users to consume the items. In this paper, we discuss the latest progress in this research direction, including potential recommendation opportunities, the existing real-world applications, as well as its relevant solutions and challenges.