Evaluation And Application Research Of Mobile Internet User Experience Based On Big Data Analysis

With the rapid development of intelligent terminal and mobile networks,the mobile Internet services also developed from the initial simple SMS and MMS business to today's mobile games,mobile twitter,mobile video and mobile positioning business.At the same time,as the operator of the mobile network,the focus on the quality of the network is also shifted from a single voice service to the mobile Internet services.Generally,however,user experience evaluation is based on the KPI indicators mapping,namely the KPI dropped call rate,completion rate,cell data throughput,customer complaints and other KPI indicators.However,KPI indicators and the actual user experience are essentially different and the traditional KPI does not reflect the true feelings of the user has become an indisputable fact.This dissertation intends to start from the rich data sources of mobile operator's network side,based on the results of large data mining,focusing on mobile Internet business,the establishment of mainstream business user perception evaluation system,and explore the network optimization based on user experience,traffic management,customer retention and other methods,making the network resources more accurate and effective,the effect of network optimization is better,jointly safeguard the fine operation of mobile operators.Firstly,this dissertation describe the detail data source of the mobile network.From the side of the BSS and OSS,the dissertation introduces the two aspects of the data source,and compares the advantages and disadvantages of various data analysis methods with the characteristics of data sources.At the same time,this dissertation analyzes the current status of the research of user experience evaluation model of mobile Internet services,analyzes and summarizes the problems existing in the current user experience evaluation model,and horizontal and vertical alignment of various research methods,analyzed advantages and disadvantages of various research methods and thus basis proposed method used in this dissertation.Secondly,this dissertation focuses on the user experience evaluation modeling method based on large data mining in the mainstream of mobile Internet services.This dissertation chooses the evaluation indicators of the mainstream services,and then the system clustering method is used to select and merge all kinds of indicators,and finally determining the indicators using to modeling.After that,this dissertation uses the AHP analytic hierarchy process to determine the user's experience weight of various indicators,and finally forms a model based on the single user's experience evaluation model.Then,based on the present data,this dissertation has completed the user level and cell level experience evaluation of a city.Finally,this dissertation analyzes the existing problems in the current network by using the model of user experience evaluation model and the application of the network,and combine the network KPI to solve the problem,and explain the important significance of the user experience evaluation model established in this dissertation.