Multimedia recommendation

Abstract

Due to the rapid growth of online multimedia information, the problem of information overload has become more and more serious in recent decades. To address this problem, various multimedia recommendation technologies have been developed by different research communities (e.g., multimedia systems, information retrieval, and machine learning). Meanwhile, many commercial web systems (e.g., Flick, Youtube, and Last.fm) have successfully applied recommendation techniques to provide users personalized multimedia content and services in a convenient and flexible way. This tutorial focuses on exploring the state-of-the-art in multimedia recommendation. We also discuss the experience gained from developing existing systems and review key challenges associated with large-scale multimedia recommendation.