Preliminary Exploration of Personalized Electronic Resource Recommendation Service Based on User Personas
With the advent of the era of information overload,the use of massive electronic resources has placed users in a dilemma of"knowledge loss".At the same time,user personas,which are used to characterize user behavior,have been widely applied in various fields.Through the analysis and mining of user data,a highly accurate user persona can be constructed,which plays an important role in providing electronic resource recommendation services to users.The user persona constructed in this paper is based on the dimensions of users and resources,and combines the basic attributes,interest attributes,and social attributes of users to construct a user similarity model to discover similar users.The similarity calculation is performed on the reading preferences of users and similar users,and finally,the electronic resources with high similarity values in the reading preferences of similar users are recommended for service.The experimental results show that personalized electronic resource recommendation services based on user personas can achieve personalized recommendation services more accurately.This is an effective exploration of providing corresponding smart services for smart libraries,which is more convenient for users to obtain data.
User profilesElectronic resourcesAccess behaviorsRecommendation services
万方数据
维普
