Artificial intelligence applications have revolutionized business, industry, and education.
Applications developed for other sectors are being adapted for education. The amount of …

Recommender Systems (RSs), which generate personalized content, have become a
technological tool with diverse applications for users. While numerous RSs have been …

Today, people frequently communicate through interactions and exchange knowledge over
the social web in various formats. Social connections have been substantially improved by …

Sequential recommender systems predict items that may interest users by modeling their
preferences based on historical interactions. Traditional sequential recommendation …

Graph-based data has gained popularity in various applications, including social networks,
recommendation systems, and knowledge graphs. Detecting missing links between nodes is …

In this paper, we develop a novel hybrid recommender system for the tourism domain, which
combines (a) a Bayesian preferences elicitation component which operates by asking the …

Tour planning has become both challenging and time-consuming due to the huge amount of
information available online and the variety of options to choose from. This is more so as …

Abstract The development of Social Media has caused an incredible change in the way
people communicate and share information. It provides a set of platforms, web-based …

The user purchase behaviors are mainly influenced by their intentions (eg, buying clothes
for decoration, buying brushes for painting, etc.). Modeling a user's latent intention can …

Artwork recommendation is challenging because it requires understanding how users
interact with highly subjective content, the complexity of the concepts embedded within the …