Among collaborative recommendation approaches, methods based on nearest-neighbors
still enjoy a huge amount of popularity, due to their simplicity, their efficiency, and their ability …

Among collaborative recommendation approaches, methods based on nearest-neighbors
still enjoy a huge amount of popularity, due to their simplicity, their efficiency, and their ability …

“Nature shows us only the tail of the lion. But I do not doubt that the lion belongs to it even
though he cannot at once reveal himself because of his enormous size.”–Albert Einstein The …

Collaborative filtering has become one of the most used approaches to provide
personalized services for users. The key of this approach is to find similar users or items …

Although Recommender Systems have been comprehensively analyzed in the past decade,
the study of social-based recommender systems just started. In this paper, aiming at …

With increasing presence and adoption of Web services on the World Wide Web, Quality-of-
Service (QoS) is becoming important for describing nonfunctional characteristics of Web …

Data sparsity, scalability and prediction quality have been recognized as the three most
crucial challenges that every collaborative filtering algorithm or recommender system …

With the widespread application of service-oriented architecture (SOA), a flood of similarly
functioning services have been deployed online. How to recommend services to users to …

As an indispensable technique in the field of Information Filtering, Recommender System
has been well studied and developed both in academia and in industry recently. However …

Aiming to alleviate data sparsity and cold-start problems of tradi-tional recommender
systems, incorporating knowledge graphs (KGs) to supplement auxiliary information has …