Recommender systems exploit interaction history to estimate user preference, having been
heavily used in a wide range of industry applications. However, static recommendation …

Recommender systems are software applications that help users to find items of interest in
situations of information overload. Current research often assumes a one-shot interaction …

People often ask others for restaurant recommendations as a way to discover new dining
experiences. This makes restaurant recommendation an exciting scenario for recommender …

Recommender systems have been researched extensively over the past decades. Whereas
several algorithms have been developed and deployed in various application domains …

In collaborative filtering recommender systems user's preferences are expressed as ratings
for items, and each additional rating extends the knowledge of the system and affects the …

Automated recommendations have become a ubiquitous part of today's online user
experience. These systems point us to additional items to purchase in online shops, they …

Recommendation systems, prevalent in many applications, aim to surface to users the right
content at the right time. Recently, researchers have aspired to develop conversational …

Conversational recommender systems aim to interactively support online users in their
information search and decision-making processes in an intuitive way. With the latest …

Conversational and question-based recommender systems have gained increasing
attention in recent years, with users enabled to converse with the system and better control …

While online content is personalized to an increasing degree, eg. using recommender
systems (RS), the rationale behind personalization and how users can adjust it typically …