The explosive growth of the world-wide-web and the emergence of e-commerce has led to the development of recommender systems—a personalized information filtering technology use...
This thesis investigates application of clustering to multi-criteria ratings as a method of improving the precision of top-N recommendations. With the advent of ecommerce sites th...
Recommender systems are important to help users select relevant and personalised information over massive amounts of data available. We propose an unified framework called Prefer...
This paper presents a novel context-based approach to find reliable recommendations for trust model in ubiquitous environments. Context is used in our approach to analyze the user...
Recommender systems are used to suggest customized products to users. Most recommender algorithms create collaborative models by taking advantage of web user profiles. In the las...
Elica Campochiaro, Riccardo Casatta, Paolo Cremone...