Network TV Recommendation System Based On User Behavior Analysis

With the spread of the Internet and the development of information technology, the storage,processing and display of information is no longer a problem, and many enterprises have stored a great number of data and contents such as business data and customer information. Before the emerging of business intelligence or data mining concepts, the data made little difference; however,driven by current information technology, more and more enterprises have learnt the importance of data to corporate decision-making, and have realized that data analysis can provide key data for corporate decision-making. Therefore, more importance has been attached to the development of business intelligence. Nowadays, the Internet has come into homes, and the speed of data transmission has upgraded from KB to MB, MB to GB level. In the past, the maximum transmission speed on the Internet could only allow obtaining information from pages; but now, we can transmit live video signal very smoothly, therefore, the network TV has gradually become popular up. We can watch movies and TV series played on web pages or by using Internet-connected TV sets or mobile clients such as cell phones, PDAs, etc. We can say, network TV, relying on its vast network resources,is gradually catching up with the fixed watching mode of traditional TV channels.This paper is intended to provide a business intelligence system, which uses the vast data sources of network TV systems as data sets and analyses the behaviors of network TV users and the operation of network TV systems, on the background of the application of business intelligence, and has a high value in application for its focus on the significance, requirements analysis and display of the system.