Recommender systems use algorithms to provide users with product or service
recommendations. Recently, these systems have been using machine learning algorithms …

Recommendation systems are gaining increasing popularity in many application areas like
e-commerce, movie and music recommendations, tourism, news, advertisement, stock …

Training datasets fundamentally impact the performance of machine learning (ML) systems.
Any biases introduced during training (implicit or explicit) are often reflected in the system's …

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 …

A group recommender system (GRS) generates suggestions for a group of individuals,
considering not only each person's preferences but also factors such as social dynamics …

The existing content-based recommendation methods have two major limitations. First, due
to the defects of the items and the user model matching algorithms, the recommendation …