Mobile Tv Customers Cluster Analysis And Content Management

With the continuous growth of mobile phone users and mobile terminals continue to improve performance, people on the phone to provide increasingly high expectations of the service, mobile phones are the communication tools from a single to a change in mobile multimedia terminals. Mobile media, which adopt mobile phone as audio-visual terminal and mobile internet as platform to deliver personalized information, is the radical innovative mass media featured with more focusing, targeting and interactive. It integrates advantages of the four major media, and will bring a audio-visual revolution and significantly impact traditional transmission models. The upcoming 3G services paved the way to the switch. An authoritative survey shows that mobile TV business, which take advantage of mobile phone's mobility to access video services anytime anywhere, is the most-concerned hot topic before 3G era and experts predicted that it will surely become an application of the time.By cluster analyzing the past consumption of customer, we can measure the preference of customer, furthermore, to make miscellaneous decisions of production and marketing.So we can distinguish between the different types of users,and then develop different content management and promotion strategiesAt present, the domestic research on mobile TV is still in the exploratory stage and most are confined to study technical standards and business models. There is a deficiency of systematic theoretical guidance, scientific industry planning and adaptive industrial policies. Therefore, it becomes a matter of urgent attention for those theoretical and practical industrial development issues that a thorough study of mobile TV user behavior, analysis of content-centric industry chain formation mechanism and its law of development, and how to provide a scientific content management model.This article is divided into seven chapters: Chapter 1 introduces the research background, research value and current status at home and abroad; chapter 2 describes technical features of mobile TV and its application models; Chapter 3 introduce definition and purpose of cluster analysis and constructed models using optimized ant colony algorithm; Chapter 4 applied the optimized ant colony algorithm model to analyze customer behavior, and analyzed user behavior based on the clustering results; Chapter 5 offered an proposal on mobile TV content planning & management system and programs recommend system; Chapter 6 provides summary and outlook for mobile TV.There is no systematic research carried out by the scientific tools on the domestic operations of the mobile TV as the whole industry is still in the period of confusion and chaos. This study will fill this gap by means of cluster analysis, using the newly proposed ant colony optimization algorithm OACA on the current user behavior analysis. And based on an analysis of the report, I research the content management and programs recommendation system, which will be valuable advice on the development of the industry.