The performance of recommender systems highly impacts both music streaming platform
users and the artists providing music. As fairness is a fundamental value of human life, there …

Psychological factors such as personality, emotions, social connections, and decision
biases can significantly affect the outcome of a decision process. These factors are also …

Personalized recommender systems have become indispensable in today's online world.
Most of today's recommendation algorithms are data-driven and based on behavioral data …

Due to the prominent role of recommender systems in our daily lives, it is increasingly
important to inform users why certain items are recommended and personalize these …

When searching and browsing the web, more and more of the information we encounter is
generated or mediated through large language models (LLMs). This can be looking for a …

AI-based recommendation algorithms have received extensive attention from both academia
and industry due to their rapid development and broad application. However, not much is …

In this study, we show that individual users' preferences for the level of diversity, popularity,
and serendipity in recommendation lists cannot be inferred from their ratings alone. We …

As argued in Chapter “Individual and Group Decision Making and Recommender Systems”,
an important function of recommender systems is to help people make better decisions. It …

Existing explainable recommender systems have mainly modeled relationships between
recommended and already experienced products, and shaped explanation types …

In recent years, diversity has attracted increasing attention in the field of recommender
systems because of its ability of catching users' various interests by providing a set of …