Research On Accurate Recommendation Service Of Online Health Community Based On User Portrait

The rapid innovation of Internet technology promotes the enhancement and progress of public Health consciousness and Health management concept,which results in the flourishing of Online Health Community(OHC).More and more web users are active in online health communities for the purposes of online social interaction,access to medical information and use of health knowledge,the online health community has gradually become an important and new channel for the public to interact and consult with each other,obtain health resources,share medical information and pay attention to health management.Especially in the face of the sudden outbreak of new coronavirus pneumonia in 2020(hereinafter referred to as “New coronavirus pneumonia epidemic”),the online health community by virtue of geographical restrictions,the screening of suspected cases,reduce exposure,avoid cross-infection,and so on,it has become an important place for people to seek medical consultation,exchange health information and pay attention to the prevention and control of epidemic situation.Many online health community platforms,such as Clove Garden,good doctor online,seeking medicine,and safe doctor online,showed a significant increase in user registration and daily visits during the epidemic period.In order to meet the health needs of the public,many online health communities have expanded their services by using big data,new media,artificial intelligence and other technologies.However,the resource supply of online health community can meet the health service demand of users to some extent,but with the increasing of health resource volume,it is more difficult for users to find the health knowledge they need.If there is not an effective balance between the resources supply of online health community and the specific service demand of users,the service quality and level of the platform will be greatly reduced.Therefore,in the face of the complex and dynamic demand characteristics of different types of users(such as elderly users,pregnant women users,students users,etc.),the online health community needs to deeply analyze the service demand characteristics of specific user groups,to provide intelligent,accurate and personalized online health services by defining the types of health services for each type of user group.Therefore,this paper introduces user profile technology to provide good theory support and method support for the intelligent,accurate and personalized recommendation service of online health community.At the same time,this study selects college students(including college students,undergraduate students and graduate students)as the research object,which is an important group of young people in today's society,a high degree of acceptance of emerging technologies and new things,and web-based knowledge search and acquisition has become an essential part of their daily learning and life.Based on this,this study from the perspective of user group portrait of university students to build a user profile-based online health community precision recommendation service model for research purposes.Through the use of Literature Research,questionnaire survey,cluster analysis,empirical research methods of four methods,combined with the theoretical basis of the model building,empirical analysis,from the following aspects of research:(1)To define the concepts of online health community,user profile and accurate recommendation service,and analyze their basic theories systematically,so as to provide theoretical basis for the construction of user profile and the framework of service model.(2)Using the market segmentation theory of VALS2 in the field of marketing as a reference,this paper designs a questionnaire,collects the data of online healthy community college students' user groups,and based on the theory of user life cycle,constructs the university students' user group portrait model by empirical analysis,finally,six specific types of portrait are obtained,which are others-guiding,advertisement-intervening,social-active,resource-acquiring,service-perceiving and mature-participating.(3)Based on the user profile model of college students,this paper proposes an online health community precision recommendation service model system based on user profile,from data processing layer to user profile layer to service recommendation layer,then to the user interface layer 4 levels respectively elaborated the concrete module of the service pattern.(4)Combining the user profile model and the precise recommendation service model,we can improve the efficiency of users' resource acquisition by improving the precise navigation function,setting up various places of friends and enriching the users' social needs on line,and establishing a complete knowledge resource database,to meet the dynamic needs of users;to integrate the support of various technologies to maintain the active level of user participation in the community;to set up an early warning mechanism for user churn,in order to improve the quality of accurate recommendation service for college students in online health community,the author puts forward some countermeasures in five aspects: ensuring the stickiness of online health community users,it provides reference for follow-up research and development of online health community platform.In a word,this paper enriches the research methods of online health community users and expands the research scope of online health community in theory and practice.