Unlike traditional recommender systems, which make recommendations only by using the relation between users and items, a context-aware recommender system makes recommendations by incorporating available contextual information ...

Contextual classification considers the information about a sample's neighborhood to improve standard pixel-based classification approaches. In this work, we evaluated four different Markovian models for Optimum-Path Forest ...

Contextual classification considers the information about a sample’s neighborhood to improve standard pixel-based classification approaches. In this work, we evaluated four different Markovian models for Optimum-Path Forest ...

An empirical model is a generalization of a probability space. It consists of a simplicial complex of subsets of a class of random variables such that each simplex has an associated probability distribution. The ensuing ...

Social networks and other digital media deal with huge amounts of user-generated contents where hate speech has become a problematic more and more relevant. A great effort has been made to develop automatic tools for its ...

Traditional machine learning algorithms very often assume statistically independent data samples. However, this is clearly not the case in remote sensing image applications, in which pixels present spatial and/or temporal ...

A recommender system is an information filtering technology which can be used to predict preference ratings of items (products, services, movies, etc) and/or to output a ranking of items that are likely to be of interest ...