In recent years there has been an enormous increase in learning resources available online
through massive open online courses and learning management systems. In this context …

Abstract Knowledge graphs have shown to be highly beneficial to recommender systems,
providing an ideal data structure to generate hybrid recommendations using both content …

Deep Learning and factorization-based collaborative filtering recommendation models have
undoubtedly dominated the scene of recommender systems in recent years. However …

Collaborative filtering models have undoubtedly dominated the scene of recommender
systems in recent years. However, due to the little use of content information, they narrowly …

Conversational recommender system is a tool to help customer in deciding products they
are going to buy, by conversational mechanism. By this mechanism, the system is able to …

Abstract Model-based approaches to recommendation can recommend items with a very
high level of accuracy. Unfortunately, even when the model embeds content-based …

Abstract As Linked Data available on the Web continue to grow, understanding their
structure and assessing their quality remains a challenging task making such the bottleneck …

Recommender systems (RS) play a focal position in modern user-centric online services.
Among them, collaborative filtering (CF) approaches have shown leading accuracy …

Processing large-scale and highly interconnected Knowledge Graphs (KG) is becoming
crucial for many applications such as recommender systems, question answering, etc …

Over the years, model-based approaches have shown their effectiveness in computing
recommendation lists in different domains and settings. By relying on the computation of …