期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2017
卷号：6
期号：3
页码：4275
DOI：10.15680/IJIRSET.2017.0603068
出版社：S&S Publications
摘要：Video is one of the most talked about items in the recommendation systems community. Videorecommendation system provides users with suitable videos to choose which is considered an effective way to gethigher user satisfaction. Ever since the Netflix Prize contest for movie recommendations, there has been growinginterests in building good video recommenders. Video recommendation can be treated as key user engagement drivingfeature for any text or multimedia driven service, be it content or search oriented. A good video recommender systemnot only increases the user engagement but also increase the revenue by making it possible to show moreadvertisements. Different from Content-Based Filtering, Collaborative filtering recommends movies according tosimilarity of users or videos. The main aim of this application is to improve the accuracy and provide fasterrecommendations using M-distance algorithm as well as traditional methods
