Social Media (SM) are the most widespread and rapid data generation applications on the
Internet increase the study of these data. However, the efficient processing of such massive …

Recommender systems have significantly developed in recent years in parallel with the
witnessed advancements in both internet of things (IoT) and artificial intelligence (AI) …

Recommender systems have been widely applied to several domains and applications to
assist decision making by recommending items tailored to user preferences. One of the …

Recommender systems play an important role in providing an engaging experience on
online music streaming services. However, the musical domain presents distinctive …

Recommender Systems (RS) help the user in the decision-making process when there is a
problem of plenty or lack of information. The context-aware recommender systems (CARS) …

Abstract In the Artificial Intelligence (AI) field, and particularly within the area of Machine
Learning (ML), recommender systems have attracted significant research attention. These …

Deciphering user purchase preferences, their likes and dislikes is a very tricky task even for
humans, making its automation a very complex job. This research work augments heuristic …

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 …

This paper investigates the impact of a recommendation system (RS) on various consumers
of a kitchen-sharing platform as regards process efficiency and consumer satisfaction. RS …

Research on recommender systems (RSs) has traditionally focused on the design of
systems capable of suggesting items of interest for users. However, often the most important …