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 challeng...Show MoreMetadata
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.
Published in: 2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS)
Date of Conference: 26-29 June 2016
Date Added to IEEE Xplore: 25 August 2016
ISBN Information: