A TV program recommendation system based on big data

Abstract

With the development of science and technology, more people especially young teenagers do not want to pay more attention to traditional TV programs. Nowadays the challenge of traditional TV station is how to attract the audience's attention, so as to improve the audience rating of tradition TV programs. This paper proposes a recommendation system, which can improve audience rating. This system mainly contains three modules. Data gathering module is responsible for collecting audience rating data about TV programs on the Internet. Data mining module is responsible for analyzing the audience ration data, and finding interesting programs that the audiences want to watch. This program recommendation system is designed to improve audience rating, and catch the attention of audiences. The system is based on massive user data, and data mining algorithms to analyze the user's interests. Compared with traditional recommendation system, it is capable for Big Data and easier for TV station to recommend TV programs in which audiences are interested, as a way to adds vitality to the television industry.