On the Internet, where the number of choices is overwhelming, there is need to filter,
prioritize and efficiently deliver relevant information in order to alleviate the problem of …

Over the past two decades, a large amount of research effort has been devoted to
develo** algorithms that generate recommendations. The resulting research progress has …

“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 …

Humans inevitably develop a sense of the relationships between objects, some of which are
based on their appearance. Some pairs of objects might be seen as being alternatives to …

A recommender system aims to provide users with personalized online product or service
recommendations to handle the increasing online information overload problem and …

Recent online services rely heavily on automatic personalization to recommend relevant
content to a large number of users. This requires systems to scale promptly to accommodate …

Recommender systems have developed in parallel with the web. They were initially based
on demographic, content-based and collaborative filtering. Currently, these systems are …

In the last 16 years, more than 200 research articles were published about research-paper
recommender systems. We reviewed these articles and present some descriptive statistics in …

Among different hybrid recommendation techniques, network-based entity recommendation
methods, which utilize user or item relationship information, are beginning to attract …

Recommender systems have become an essential tool to help resolve the information
overload problem in recent decades. Traditional recommender systems, however, suffer …