Feature-based matrix factorization techniques such as Factorization Machines (FM) have
been proven to achieve impressive accuracy for the rating prediction task. However, most …

Recently, there has been growing interest in recommender systems (RS) and particularly in
context-aware RS. Methods for generating context-aware recommendations are classified …

This paper presents a design and implementation of a multitype, proactive and context-
aware recommender system in the environment of Internet of Things (IoT). The main features …

Food based dietary guidelines are insufficiently followed by consumers. One of the principal
explanations of this failure is that they are too general and do not take into account eating …

The high adoption of smart mobile devices among consumers provides an opportunity for e‐
commerce retailers to increase their sales by recommending consumers with real time …

Recommenders, as widely implemented nowadays by major e-commerce players like Netflix
or Amazon, use collaborative filtering to suggest the most relevant items to their users …

Recommender systems have become indispensable for services in the era of big data. To
improve accuracy and satisfaction, context-aware recommender systems (CARSs) attempt to …

Recommender systems have been widely applied to assist user's decision making by
providing a list of personalized item recommendations. Context-aware recommender …

Abstract Recommender Systems (RSs) are new types of internet-based software tools, used
to provide personalized recommendations to users by handling information overload …

The problem of different contextual information to influence the user‐item‐context
interactions at varying degrees in context‐aware recommender systems is addressed. To …