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

Over the years, personalisation in e‐learning has evolved as a promising paradigm for
matching learners' specific requirements. Although many literature reviews on personalised …

This survey paper provides a comprehensive analysis of the evolution and current
landscape of recommendation systems, extensively used across various web applications. It …

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

In order to alleviate the network information overload, recommender system becomes
widespread in personalized recommendation. However, due to the increase of the number …

Recommender systems are an effective tool to resolve information overload by enabling the
selection of the subsets of items from a universal set based on user preferences. The …

In the era of internet and big data, recommender systems are necessary to filter out useless
information. Collaborative filtering (CF) is one of the most successful technique used in …

Recommender systems utilizing explicit feedback have witnessed significant advancements
and widespread applications over the past years. However, generating recommendations in …

Recommender systems are decision support systems that help users to identify items of
relevance from a potentially large set of alternatives. In contrast to the mainstream …

Negative information plays an important role in the way we express our preferences and
desires. However, it has not received the same attention as positive feedback in …