| In recent years,the rapid development of communication technology and Internet technology,IPTV has entered more and more homes,and has become one of the important commercial services of telecommunications operators.With the expansion of the IPTV market,competition among operators is becoming increasingly fierce,and users are increasingly demanding services.It is important to expand the user scale,quickly occupy the market,and improve the quality of user experience to obtain user recognition of the business.At the same time,the advent of the era of big data has brought new challenges to operators.Traditional data processing platforms and technologies are difficult to adapt to massive data and complex business environments.Therefore,combining big data-related technologies to build systems and achieve quality of user experience Active monitoring has become an urgent need for telecom operators.First,this thesis introduces the research status of user experience quality and IPTV user experience quality monitoring based on big data,and summarizes the algorithms related to user experience quality assessment and existing big data related technologies.Secondly,this thesis analyzes the system requirements,and carries out the overall system design and detailed design of each module of the system,including data acquisition and preprocessing module design,data storage module design,data analysis module design,and data visualization module design.This thesis selects subjective and objective factors that affect user experience,applies machine learning algorithms to establish a user experience quality(QoE)evaluation model,and makes the calculation results closer to user perception.At the same time,it optimizes classic algorithms based on the imbalance of business data in actual operations.And improvement,and the optimization algorithm CS-AdaBoost-BP is applied to the IPTV service data,which improves the accuracy of the model calculation.Finally,this thesis completes the implementation and testing of the IPTV user experience quality monitoring system based on big data.Based on the system design,by building a cluster,installing and deploying big data components,designing and writing business logic code,the overall function from data collection to visualized display of results is achieved,and complete the system function test and performance test,ensure the system’s effectiveness and reliability. |
