Recommendation systems have witnessed significant advancements and have been widely
used over the past decades. However, most traditional recommendation methods are task …

The recommender systems aim to predict potential demands of users by analyzing their
preferences and provide personalized recommendation services. User preferences can be …

Researchers face millions of research papers on various digital libraries. Therefore, finding
relevant research work that meets the preferences of a researcher is a challenging task …

Many effective tools in fuzzy soft set theory have been proposed to handle various
complicated problems in different fields of our real life, especially in decision making …

With the emergence of online social networks and microblogging websites, user interest
mining has been an active research topic for the past few years. However, most of the …

In the world of Big Data, a tool capable of filtering data and providing choice support is
crucial. Recommender Systems have this aim. These have evolved further through the use …

Due to the expansion of e-business, the availability of products on the internet has massively
increased. Finding suitable stuff from the vast array of products available on the internet is a …

The variety and plethora of research papers available on the Web motivated researchers to
propose models that could assist users with personalized citation recommendations. In …

Collaborative filtering has been the most straightforward and most preferable approach in
the recommender systems. This technique recommends an item to a target user from the …

This survey provides an exhaustive exploration of the evolution and current state of
recommendation systems, which have seen widespread integration in various web …