Recommending items to users: an explore/exploit perspective

Traditionally, recommender systems for the web deal with applications that have two dimensions, users and items. Based on access data that relate these dimensions, a recommendation model can be built and used to identify a set of N items that will be of ...

Tags are an important information source in Web 2.0. They can be used to describe users' topic preferences as well as the content of items to make personalized recommendations. However, since tags are arbitrary words given by users, they contain a lot ...

Sales diversity is considered a key feature of Recommender Systems from a business perspective. Sales diversity is also linked with the long-tail novelty of recommendations, a quality dimension from the user perspective. We explore the inversion of the ...