Video on demand recommender system for internet protocol television service based on explicit information fusion

摘要: Abstract Internet protocol television (IPTV) provides video on demand (VOD), internet service, and real-time broadcasting to users as a service that combines communication technology. Among various services, the sales of VOD are profitable because VODs offer relatively strong direct revenue models in IPTV services. However, development recommender system for is highly challenging owing lack explicit preference information an environment. Previous studies systems have attempted solve data sparsity problem through implicit information; however, it better utilize improve performance system. Recently, providers provided their own over-the-top (OTT) services such items can be combined. Therefore, we proposed novel fusion method integrates both OTT In addition, utilized probabilistic matrix factorization, guarantees high most systems, algorithm this study. Finally, conducted comparative evaluations based metrics validated contribute