LEVERAGING ONLINE SOCIAL RELATIONS TO IMPROVE THE DIVERSITY OF PERSONALIZED RECOMMENDATION LIST

摘要

Recommender systems typically focus on using accuracy as the key metric to evaluate the performance of the recommendations. However, recent studies suggest that recommending a diverse list of products enhances user satisfaction and is positively associated with customer retention rates. In this study, we propose to leverage the social relations of a user in an online environment to improve the diversity of personalized recommendation list. Our preliminary empirical results indicate that our proposed approach performs well in increasing the recommendation diversity while maintaining comparable level of accuracy.