Recommender systems are efficient tools for filtering online information, which is
widespread owing to the changing habits of computer users, personalization trends, and …

In our work, we have presented two widely used recommendation systems. We have
presented a context-aware recommender system to filter the items associated with user's …

Recommender systems have the effect of guiding users in a personalized way to interesting
objects in a large space of possible options. Content-based recommendation systems try to …

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 …

Content-based recommender systems (CBRSs) rely on item and user descriptions (content)
to build item representations and user profiles that can be effectively exploited to suggest …

In recent times, the recommender systems (RSs) have considerable importance in
academia, commercial activities, and industry. They are widely used in various domains …

Recommendation System is a major area which is very popular and useful for people to take
proper decision. It is a method that helps user to find out the information which is beneficial …

In recent years, the sentiment analysis has been explored by several Internet services to
recommend contents in accordance with human emotions, which are expressed through …

The problem of information overload motivated the appearance of Recommender Systems.
From the several open problems in this area, the decision of which is the best …

Recommender systems have been developed in variety of domains, including
asynchronous discussion group which is one of the most interesting ones. Due to the …