Research on Personalized Recommendation Method for Literature Resources in Smart Libraries Based on User Profile
This article focuses on the problem of low recommendation accuracy in existing recommendation methods,and conducts research on the design of personalized recommendation methods for literature resources in smart libraries.Firstly,construct a user interest feature model through the application of user profiling.Then extract the features of literature resources,match them with user interest features,and achieve personalized recommendation of literature resources.Finally,comparative experiments are carried out to prove the progressiveness of the proposed method.The experimental results show that the new recommendation method can effectively promote the improvement of accuracy in literature resource recommendation,and the application effect is good.
user profileliterature resourcesrecommendationpersonalizationsmart library
NETL
NSTL
万方数据
