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

In this article, we suggest a novel deep learning recommendation framework that
incorporates contextual information into neural collaborative filtering recommendation …

Depending on the Internet as the main source of information regarding all aspects of our life
is becoming a trend. People seek relevant information, suggestions, and recommendations …

Recommender systems (RSs) are systems that produce individualized recommendations as
output or drive the user in a personalized way to interesting or useful objects in a space of …

Location-based social networks (LBSNs) make it possible for people to share their visited
places by uploading the check-in information. To improve the efficiency of recommendation …

Personality traits have been demonstrated as one of the effective human factors in the
process of decision making. Personality-aware recommendation models have been built for …

In today's competitive world it is must for students to meet their respective needs from
universities. For this, student should know the different colleges, different fields to have clear …

The availability of huge volumes of online research papers over scholarly communities has
been increasing rapidly with the evolution of the Internet. Meanwhile, several researchers …

Recently, Recurrent Neural Network (RNN) leads to a paradigm shift in recommendation
tasks, which achieves state-of-the-art performance compared with traditional methods. In …

Recommender systems were devised to provide personalized recommendations on suitable
items that would match the individual users' interests. The standard recommendation …