Users of sentiment analysis applications are interested in opinions of individual aspects (eg,
excellent mileage) of a target entity rather than in their polarity (eg, 56% are positive). This …

Explanations can help people to make better choices, but their use in recommender systems
has so far been limited to the annotation of recommendations after they have been ranked …

Music content creation, publication and dissemination has changed dramatically in the last
few decades. Huge amounts of information about music are being published daily in online …

Millions of people interact and share interesting information every day in the Social Web.
From daily conversations to comments about products in e-commerce sites, the content …

Music content creation, publication and dissemination has changed dramatically in the last
few decades. Huge amounts of information about music are being published daily in online …

Social recommender systems harness knowledge from social content, experiences and
interactions to provide recommendations to users. The retrieval and ranking of products …

Providing explanations based on user reviews in recommender systems may increase
users' perception of transparency. However, little is known about how these explanations …

In the digital era, users have, more than at any point in history, a large amount of products or
services to choose from. Recommender systems help to overcome this problem by …

With the arrival of the digital era, users are faced with an ever greater choice of products and
services. The number of products and services (items) in many cases exceeds the …

Millions of people interact and share interesting information every day in the Social Web.
From daily conversations to comments about products in e-commerce sites, the content …