Recommender Systems Questions
Diversity-aware recommender systems aim to provide recommendations that not only satisfy users' preferences but also promote diversity in the recommended items. These systems consider the diversity of items based on various dimensions such as genre, topic, popularity, or novelty. By incorporating diversity, recommender systems can offer a wider range of options to users, preventing the problem of over-specialization and filter bubbles. This approach helps users discover new and unexpected items, enhancing their overall experience and avoiding monotony in recommendations.