When people use web search engines to find information on debated topics, the search
results they encounter can influence opinion formation and practical decision-making with …

Recommender systems suggest items, such as movies or books, to users based on their
interests. These systems often suggest items that users are either already familiar with or …

In the recommender systems field, it is increasingly recognized that focusing on accuracy
measures is limiting and misguided. Unsurprisingly, in recent years, the field has witnessed …

Recommender systems can assist in various user tasks and serve diverse values, including
exploring the item space. Serendipity has recently received considerable attention, often …

The RecSys Challenge 2024, co-organized by the Danish news outlet Ekstra Bladet, called
for participants to develop a news recommender system that accurately predicts which news …

Serendipity has been recognized as a valuable property of recommender systems. While
there is a lack of consensus on the precise definition of serendipity, it is often conceptualized …

Recommender systems play a crucial role in our daily lives, constantly evolving to meet the
diverse needs of users. As the pursuit of improved user experiences continues, metrics such …

The primary goal of Recommender Systems is to suggest the most suitable items to a user,
aligning them with the user's interests and needs. RSs are essential for modern e …

In the past, recommender systems were primarily focused on optimizing accuracy. However,
in recent years, there has been an increasing awareness that considerations beyond …

Recommender systems are widely used in various applications, such as online shop**,
social media, and news personalization. They can help systems by delivering only the most …