The impact of data characteristics on the performance of classical recommender systems
has been recently investigated and produced fruitful results about the relationship they have …

As of today, most movie recommendation services base their recommendations on
collaborative filtering (CF) and/or content-based filtering (CBF) models that use metadata …

Despite of tourism infrastructure and software, the development of tourism is hampered due
to the lack of information support, which encapsulates various aspects of travel …

Recommender Systems are decision support tools that adopt advanced algorithms in order
to help users to find less-explored items that can be interesting for them. While …

Recommender systems (RSs) are personalized information search and discovery
applications helping users to identify and choose useful items and information. In this paper …

This book is an introduction to social data analytics along with its challenges and
opportunities in the age of Big Data and Artificial Intelligence. It focuses primarily on …

In recent years, an event‐based social network recommendation system has attracted more
and more researchers' attention. Most EBSN recommendation systems mainly focus on …

Personalized recommender systems rely on knowledge of user preferences to produce
recommendations. While those preferences are often obtained from past user interactions …

A challenge for many young adults is to find the right institution to follow higher education.
Global university rankings are a commonly used, but inefficient tool, for they do not consider …

The growth of online job-posting repositories provided job-seekers with access to a large
number of potential jobs. User assessment of recommended jobs becomes especially a …