The evaluation of recommender systems is an area with unsolved questions at several
levels. Choosing the appropriate evaluation metric is one of such important issues. Ranking …

The evaluation of Recommender Systems is still an open issue in the field. Despite its
limitations, offline evaluation usually constitutes the first step in assessing recommendation …

In information retrieval, pseudo-relevance feedback (PRF) refers to a strategy for updating
the query model using the top retrieved documents. PRF has been proven to be highly …

Image tag recommendation, aiming at assigning a set of relevant tags for images, is a useful
way to help users organize images' content. Early methods in image tagging mainly …

Recommender systems are a growing research field due to its immense potential
application for hel** users to select products and services. Recommenders are useful in a …

Often people might not be able to express themselves properly on social media, like not
being able to think of appropriate words representative of their emotional state. In this paper …

Recommender Systems have to deal with a wide variety of users and user types that
express their preferences in different ways. This difference in user behavior can have a …

When looking for recently published scientific papers, a researcher usually focuses on the
topics related to her/his scientific interests. The task of a recommender system is to provide a …

We investigate a novel perspective to the development of effective algorithms for contact
recommendation in social networks, where the problem consists of automatically predicting …