Recommender systems have become an important research field since the emergence of
the first paper on collaborative filtering in the mid-1990s. Although academic research on …

Intelligent data handling techniques are beneficial for users; to store, process, analyze and
access the vast amount of information produced by electronic and automated devices. The …

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

The new user cold start issue represents a serious problem in recommender systems as it
can lead to the loss of new users who decide to stop using the system due to the lack of …

Online business transactions and the success of e-commerce depend greatly on the
effective design of a product recommender mechanism. This study proposes a social …

Recommender systems (RSs) are programs that apply knowledge discovery techniques to
make personalized recommendations for user's information on the web. In online sharing …

Internet has significantly influenced the tourism sector providing a great variety of services
and products online. However, the number of choices has increased so dramatically that is …

The demand for ubiquitous information processing over the Web has called for the
development of context-aware recommender systems capable of dealing with the problems …

Recommender systems are programs that aim to provide personalized recommendations to
users for specific items (eg music, books) in online sharing communities or on e-commerce …

The trust network is a social network where nodes are inter-linked by their trust relations. It
has been widely used in various applications, however, little is known about its structure due …