The recent rapid growth of the Internet content has led to building recommendation systems
that guide users to their needs through an information retrieving process. An expert …

The recommender system (RS) filters out important information from a large pool of
dynamically generated information to set some important decisions in terms of some …

Recommender Systems have gained popularity in recent years due to their ability to
expedite users' selection processes quickly. Traditional recommender systems mainly focus …

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 …

Due to a busy schedule, people highly dependent on various kinds of online
recommendations to utilize their precious time. The collaborative filtering is wide as the …

Recommender Systems (RecSys) provide suggestions in many decision-making processes.
Given that groups of people can perform many real-world activities (eg, a group of people …

We propose a novel recommendation approach based on chronological cohesive units
(CCUs) of content consuming logs. Chronological cohesive units are defined as sub …

Group recommender system provides suggestions for a group of users by exploring the
choices of individual users of the group. Popularity of group recommender systems is …

Internet has open platforms for various domains to interact with each other. e-leaning is a
domain which consistently getting attention because of “Learn any-time, anywhere” …

Abstract Group Recommendation Systems (GRS) are ubiquitously available to give
recommendations to users indulging in group activities. These systems recommend items …