A good content recommendation system is key for any content provider. Machine Learning video recommendations provide a unique opportunity for broadcasters, Pay-TV operators, TV Networks, and any content distributor to increase engagement and reduce churn through content personalization.
Currently, most recommendation systems operate using explicit information provided by the user about their preferences (for example, by scoring previously watched content) using a technique known as collaborative filtering.
Recently there has been a lot of talk about personalization in the world of video. One of the questions that my colleagues and I have
Personalisation is currently a trendy topic and is recognised as one of the key means to improve engagement and reduce churn for video service providers.
Nobody can dispute that Over-The-Top (OTT) video distribution is here to stay. In most markets today, TV and video consumption via internet-connected devices is commonplace in
Today is my first day as CEO of JUMP TV, the new company I have just founded together with my good partners Jesús Herrero (COO)