The Persona Based On Big Data Analysis Research And Application

In recent years,with the development of technologies such as the Internet of Things,cloud computing,and big data,using data to lead innovation and data-driven development has become a symbol of the era of big data.The state proposes an"Internet+" action plan to encourage the active integration of traditional industries with the Internet.In addition,the life of Internet products has prompted the huge personal data generated by people in the network platform.The hidden user needs behind these user-generated data stimulate enterprises to explore the application of product and user interaction through machine learning and data mining technology.Excavating the value of massive user data has become the key to the transitional transformation of enterprises in the era of big data.The User Portrait Tool is an effective guide tool for helping companies understand users,and is widely used in product operations and experience design.In the Internet non-big data environment,due to the limitations of data technology,enterprises construct user images mainly through qualitative research methods such as field investigation.However,in today’s efficiency-oriented work environment,user images created by qualitative research methods cannot adapt to sudden changes in business needs.On the other hand,big data resources drive companies to change the way they analyze user needs.For enterprises,it is meaningful to use big data technology to analyze user characteristics,behaviors,and requirements to build a user portrait model.This paper first reviews the user’s portraits and discusses the characteristics of user portraits in the context of big data.By analyzing the research of user portraits by domestic and foreign research scholars.And determining the theory of Andersen’s participation in user portrait research,the use of big data technology and professional subjective thinking ability to drive together to create user portraits.Then,by analyzing the advantages and disadvantages of the non-big data user’s portrait,the structured user portrait framework suitable for the big data user portrait is obtained.And the related research on the content description in the portrait frame is summarized,and the content description set table of the user portrait is analyzed.Subsequently,in the study of the design and application meaning of big data user portraits,it is found that the big data user portrait has limitations in the design and the application,and proposes a method of optimizing the big data user image prototype using the qualitative user research method to improve.The lack of application of big data user images in the design field.Finally,the above research theory is applied to practical projects to test its effectiveness.User image prototypes created using big data technology based on the business needs of the project.Later,using sociological research methods to take advantage of leading users to optimize user portrait prototypes to form a comprehensive picture of big data users.It is practically instructive to verify the created portraits by using comparative experiments.The significance of this paper lies in the method of creating big data user portraits,combining quantitative research methods such as data mining,machine learning and natural language processing,and qualitative research methods of anthropology and sociology.Combining the high-performance advantages of big data with the heuristic advantages of qualitative research makes the big data user portrait tools more comprehensive,effective and scientific and innovative in design applications.