基于知识图谱的智慧图书馆文献资源个性化推荐方法  

The Personalized Recommendation Method of Literature Resources in Intelligent Library Based on Knowledge Graph

作　　者：和欣 HE Xin(Library,Shenyang University of Chemical Technology,Shenyang 110142,China)

机构地区：[1]沈阳化工大学图书馆,辽宁沈阳110142

出　　处：《数字通信世界》2024年第7期79-81,共3页Digital Communication World

摘　　要：为提高用户对智慧图书馆服务的满意度,该文以某智慧图书馆建设为例,引入知识图谱理论,开展文献资源个性化推荐方法的设计研究。首先构建智慧图书馆文献资源知识图谱,抽取知识图谱中的核心内容;然后将文献资源中的知识点与其他知识点建立联系,形成知识网络;最后通过对文献资源的深入分析和挖掘,构建用户资源关联信息,根据用户与不同类别文本之间的相似度或匹配度,实现对资源的个性化推荐。实验结果表明:应用该文设计的个性化推荐方法,可以根据用户的兴趣、需求和行为习惯等信息,主动向用户推送符合其需求的文献资源,推荐的资源与用户需求资源相似度较高,应用效果较好。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.

关 键 词：知识图谱 特征抽取 推荐方法 个性化 文献资源 智慧图书馆 

分 类 号：G250.7[文化科学—图书馆学] TP391[自动化与计算机技术—计算机应用技术]