Recommender Systems (RS) play an integral role in enhancing user experiences by
providing personalized item suggestions. This survey reviews the progress in RS inclusively …

In recent years, location-based social networks (LBSNs) that allow members to share their
location and provide related services, and point-of-interest (POIs) recommendations which …

Aiming to solve the problem that ideological and political education courses in universities
are not targeted enough and cannot form personalized recommendations, this paper …

Personalized courses recommendation technology is one of the hotspots in online
education field. A good recommendation algorithm can stimulate learners' enthusiasm and …

Abstract Web users are flooded with information on the internet, and they feel overwhelmed
by the different choices they have to make online daily. Recommender systems come to their …

The e‐commerce recommendation system mainly includes content recommendation
technology, collaborative filtering recommendation technology, and hybrid recommendation …

In the current digital landscape, both information consumers and producers encounter
numerous challenges, underscoring the importance of recommender systems (RS) as a vital …

Many tourists who travel to explore different cultures and cities worldwide aim to find the best
tourist sites, accommodation, and food according to their interests. This objective makes it …

Recommender system (RS) has grown widely in various communities over the last few
years. It creates curiosity among the researchers due to the recent growth of various …

A recommender system (RS) is a subcategory of an information filtering system that attempts
the prediction of the score or the importance given to an item by a user. RS has garnered the …