Abstract
With the widespread availability of media technologies, such as real-time streaming, new IoT devices and smartphones, multimedia data are extensively increased and the big multimedia data are rapidly spreaded over various social networks. Thus, different multimedia recommender systems have been emerging to help users select the useful multimedia objects. However, due to distinct features of multimedia objects, it is difficult to conduct a proper evaluation for the multimedia recommender systems, and the evaluation from the general recommender systems might not be totally adopted to evaluate them. In this paper, we therefore review and analyze the evaluation criteria that are used in the previous multimedia recommender system papers. Based on the review, we propose a set of the practical advices to lead practitioners and researchers to perform evaluations for multimedia recommender systems.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
