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面向用户需求的有线电视用户离网预警管理系统建设
引用本文:韩凌.面向用户需求的有线电视用户离网预警管理系统建设[J].电视技术,2017,41(7).
作者姓名:韩凌
作者单位:格兰研究,北京,100866
摘    要:随着有线电视的一元化收视格局被打破,用户离网问题变得日益严重,如何通过大数据技术和数据挖掘技术来降低用户流失率、提高用户的净推荐值已经成为影响广电运营商发展的首要因素,从有线电视用户收视行为的演变出发,分析了解决有线电视用户离网问题的路径和方法.第一部分介绍了有线电视用户离网现状与原因,从视频收视格局的变化出发,剖析了有线电视用户离网的现状和原因.第二部分介绍了建设有线电视用户离网预警系统的必要性和系统构成,分析了以往离网研究存在的问题,并介绍了格兰研究最新研发的大数据用户离网预警管理系统和online在线服务系统.第三部分介绍了大数据离网预警管理系统的关键技术和物理架构.第四部分介绍了离网预警管理系统的应用,分别阐述了离网用户挽留方案的制定和部门间的无障碍数据应用.

关 键 词:有线电视  用户需求  离网预警

Construction of CATV user off-grid early warning management system for user demand
HAN Ling.Construction of CATV user off-grid early warning management system for user demand[J].Tv Engineering,2017,41(7).
Authors:HAN Ling
Abstract:With CATV unified viewing pattern is broken,theproblem of user off-grid becomes more and more serious,how to reduce user churn rate and improve user net value through Big Data and Data Mining becomes the primary factor affecting the development of CATV operators.Based on the evolution of CATV users' viewing behavior,this paper analyzes the path and method of solving the problem of CATV user off-grid.This paper has four parts.The first part shows the status and causes of CATV user off the grid,and dissect this situation according to the variety of viewing pattern of video.The second part presents system components and necessity of construction about CATV user off-grid early warning system.Meanwhile it analyzes the existing problems in previous off-grid research,and shows CATV user off-grid early warning management system based on Big Data and online service system that Guideline Research develops the latest results.The third part introduces the key technology and physical structure of CATV user off-grid early warning management system based on Big Data.The fourth part introduces the application of CATV user off-grid early warning management system,and elaborates a method of the development of off-grid user retention program and application with interdepartmental accessibility.
Keywords:CATV  demand for user  off-grid early warning
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