Group recommender systems have been designed which, instead of suggesting one or
more items to people individually, concurrently recommend them to a group of people who …

Recommender systems are known for hel** e-commerce and entertainment sits to provide
excellent services into their clients by finding those interests in a short time as possible …

Collaborative filtering which is the most successful technique of the Recommender System,
has recently attracted great attention, especially in the field of e-commerce. CF is used to …

Planning a personalized itinerary that satisfies the preferences and limitations of a tourist
can be a complex task. The challenge is further compounded by the lack of information …

Abstract The prevalence of Recommender Systems (RS) has surged due to the widespread
growth of the Internet and its related technologies. The efficiency of the RS is dependent on …

Demand for personalized recommendation systems elevated recently by e-commerce, news
portals etc., to grab the customer interest on the sites. Collaborative filtering proves to be …

A recommender system is an information selection system that offers preferences to users
and enhances their decision‐making. This system is commonly implemented in human …

The majority of existing recommender systems rely on user ratings, which are limited by the
lack of user collaboration and the sparsity problem. To address these issues, this study …

The assignment of a fixed weight value to an attribute (or variable) is not always considered
reasonable, as it may not effectively preserve user similarity, potentially resulting in a decline …

Abstract Implicit Trust-Network approach and Recommendation Methodology are employed
following the building of a recommender system to improve prediction precision and …