Research On Personalized Recommendation Service Of Self-service Library From The Perspective Of User Profile

With the continuous development of cloud computing technology,the service modes of various industries are becoming more and more diverse,and interactive services centered on user experience have become one of the hotspots of research at this stage.As a tool to abstract user information,describe user image,and highlight user characteristics,user profile is widely used in personalized recommendation services,and it also injects new vitality into the innovation and development of self-service library services.The self-service library builds a user profile model,takes user data as a reference,and deeply understands users' interests and preferences,providing new references for the realization of two-way matching between self-service library resources and user needs.This paper introduces user profiles into the field of self-service library services,adopts a combination of qualitative and quantitative analysis methods,and follows the process from theoretical foundation to model construction to empirical research.The significance of this paper is to sort out the research status of user profiles and self-service library services at home and abroad,and expounds related concepts such as user profiles and self-service library services.Secondly,combining the self-service library with user profiles,the necessity of user profiles in self-service libraries is proposed,and then the functions of user profiles in the personalized recommendation service of self-service libraries are expounded,including integrating user data,locating target users and assisting personality.It provides a personalized recommendation service as the basis for the construction of the user profile model of the self-service library.Thirdly,based on the introduction of user profile,this paper introduces the profile model architecture,expounds the design and weight setting of the user profile label system in the self-service library,uses the K-means algorithm to perform cluster analysis on the users of the self-service library,and then proposes the similarity and preference of users.This paper analyzes the user's satisfaction with the scheme by means of a questionnaire survey,and finally puts forward the optimization strategy of the personalized recommendation service of the self-service library,in order to realize the innovation of the personalized recommendation service of the self-service library.