Recommender systems are a key technology for many applications, such as e-commerce,
streaming media, and social media. Traditional recommender systems rely on collaborative …

Recommendation algorithms are data filtering tools that make use of algorithms and data to
recommend the most relevant items to a particular user. The algorithm-driven …

The development of Social and Emotional competences of students can significantly
improve their learning and social outcomes. This prompts for tools to assist tutors in …

There are mounting concerns that personalized recommenders contribute to population
differentiation and polarization by creating “information cocoons” that insulate people from …

To achieve the personalisation recommendation, modem recommendation models should
consider the user's preference for item attributes and dynamic changes in preferences. 1RS …

Recommender systems are used with increasing frequency in a wide variety of domains
ranging from e-commerce to tourism, healthcare and online learning. However, the …

The integration of digital technologies in education has led to major changes, including the
rise of project-based work. However, learners often face challenges in navigating through …

CRS strives to return the most relevant recommendations to users through a multi-turn
interactive conversation. The Covid-19 pandemic has undoubtedly accelerated the pace of …

The development of Social and Emotional competences of students can significantly
improve their learning and social outcomes. This prompts for tools to assist tutors in …