Recommender systems use algorithms to provide users with product or service
recommendations. Recently, these systems have been using machine learning algorithms …

Exploiting temporal context has been proved to be an effective approach to improve
recommendation performance, as shown, eg in the Netflix Prize competition. Time-aware …

In this chapter, we give an overview of the main Data Mining techniques used in the context
of Recommender Systems. We first describe common preprocessing methods such as …

Recommender system (RS) has emerged as a major research interest that aims to help
users to find items online by providing suggestions that closely match their interest. This …

For decades large corporations as well as labor placement services have maintained
extensive yet static resume databanks. Online professional networks like LinkedIn have …

We present multi-modal adversarial autoencoders for recommendation and evaluate them
on two different tasks: citation recommendation and subject label recommendation. We …

It is well known that there are some maternal and fetal issues that directly influence preterm
births. However, all the variables provoking it are not completely determined. On the other …

Fall detection represents an important issue when dealing with Ambient Assisted Living for
the elder. The vast majority of fall detection approaches have been developed for healthy …

As an essential branch of artificial intelligence, recommendation systems have gradually
penetrated people's daily lives. It is the active recommendation of goods or services of …

We propose four fuzzy-logic based models of tag recommendation, which are based on the
interpretation of word frequency as a fuzzy membership function, and provide experimental …