The Personalized Recommendation Method of Literature Resources in Intelligent Library Based on Knowledge Graph
In order to improve users'satisfaction with the smart library,this paper takes the construction of a smart library as an example,introduces the knowledge graph theory,and carries out the design and research of the personalized recommendation method of literature resources.Firstly,the knowledge map of the literature resources of the smart library is constructed,and the core content of the knowledge map is extracted.Then the knowledge points in the literature resources are connected with other knowledge points to form a knowledge network.Finally,through in-depth analysis and mining of literature resources,the association information of user resources is constructed,and personalized recommendation of resources is realized according to the similarity or matching degree between users and different types of texts.The experimental results show that the personalized recommendation method designed in this paper can be applied to actively push literature resources that meet the needs of users according to their interests,needs and behavior habits and other information.The recommended resources are highly similar to the resources required by users,and the application effect is good.