A comparative study of video recommender systems in big data era

Recently, due to the wide spread of high-bandwidth access to the Internet, and abundant generation of various kinds video contents, we live in a big data era, especially in video contents. There are too much videos already, but we are even unable to know which video is good for me now. In the coming big data era, video contents providers should develop efficient recommendation system to be competitive and survive. In the paper, we compared video recommendation technologies of four famous companies: Netflix, Google (YouTube), Hulu, and Amazon in order to understand the basic differences between their recommendation algorithms and investigate the pros and cons. Most recommendation algorithms adopted collaborative filtering, but there are some differences. These days, as the data of user behavior can be gathered more easily, meta data play more important roles than recommendation algorithms.