Abstract Recommender Systems (RSs) are software tools and techniques providing
suggestions of relevant items to users. These systems have received increasing attention …

Since their launch in the early 1990's, recommender systems (RSs) have played an
essential role in information filtering and providing personalized information to users by …

There is an increasing amount of multimedia content available to end users. Recommender
systems help these end users by selecting a small but relevant subset of items for each user …

Affective labeling of multimedia content has proved to be useful in recommender systems. In
this paper we present a methodology for the implicit acquisition of affective labels for …

This paper outlines the educational advantages provided by adaptive systems and stresses
the importance of the user model in the task of adaptation. The paper also establishes a …

Internet protocol television (IPTV), the television services through the Internet, has recently
gained increasing popularity. One key advantage of IPTV over the traditional terrestrial TV …

With the steadily increasing amount of digital multimedia content, the user will be more and
more overstrained. This applies to content being permanently available like videos of online …

The PhD research presented in this paper discusses the inclusion of affective computing in
multimedia recommender systems. Our objective is to fill the missing gaps of the scenario …

The large amounts of TV, radio, games, music tracks or other IP based content becoming
available in DVB-H mobile digital broadcast, offering more than 50 channels when adapted …

Affective labeling of multimedia content can be useful in recommender systems. In this paper
we compare the effect of implicit and explicit affective labeling in an image recommender …