Research On The Application Of Personalized Recommendation Mechanism Based On User Experience In News APP

With the continuous development of mobile Internet,mobile devices become more and more convenient,and the advantages of fixed devices are gradually covered by the development of mobile devices.The mobile news client has become the main source channel for users to obtain news,which can provide users with real-time and mobile reading experience and meet the needs of users to browse news anytime and anywhere.At present,the development trend of information fragmentation and the explosion-like growth have brought inconvenience to users to receive information.In order to better provide users with information services and meet their personalized needs,personalized recommendation system has emerged,providing users with accurate content distribution,and quickly occupying the market with its efficient operation,which has become a technical means for news clients to attract users.With the more and more extensive application of personalized recommendation,the research of personalized recommendation has added many angles.From the perspective of user experience,combined with the theory of "use and satisfaction" and equipped with the technology acceptance model,this paper selects three typical representatives of personalized news recommendation platforms,including today’s headlines,a little information and daily express,to study the user motivation and demand satisfaction of these platforms.First,interview the users of these platforms,analyze and sort out the interview contents and related literature at home and abroad,and make a questionnaire.After testing the rationality of the questionnaire,the formal questionnaire will be issued.After the questionnaire was collected,SPSS software was used to sort out,analyze and calculate the collected data.Based on the theory of "use and satisfaction" and "technology acceptance model",an empirical study was conducted around the basic information,motivation,satisfaction,perceived usefulness and perceived ease of use of users,and finally the influencing factors of users’ needs at different levels were further discussed through the discovery and analysis of data results.Then,the dilemma of personalized recommendation mechanism in the APPlication of news app is analyzed,and the optimization of personalized recommendation in the application of news client is discussed.The following conclusions are drawn: while personalized recommendation mechanism brings great convenience,there are also dilemmas such as "filtering bubbles" caused by algorithm limitations,insufficient quality of pushed content affecting users’ use and ethical problems caused by power transfer algorithm.In order to better optimize the APPlication of personalized recommendation mechanism in news app,the author puts forward the following countermeasures:strengthening users’ information literacy to puncture "filtering bubbles",insisting on "content is king" to ensure information value,and forming reasonable joint supervision by multi-party supervision.Technology is a double-edged sword.Only by avoiding its disadvantages as much as possible and giving full play to its advantages can technology be better used by people.