基于随机游走模型的高校图书馆知识发现系统构建  

Construction of Knowledge Discovery System in University Library Based on Random Walking Model

作　　者：刘爱琴[1] 贾一帆 冷长青 Liu Aiqin;Jia Yifan;Leng Changqing(School of Economics and Management,Shanxi University,Taiyuan 030006,China)

机构地区：[1]山西大学经济与管理学院,山西太原030006

出　　处：《现代情报》2020年第5期96-103,共8页Journal of Modern Information

基　　金：山西大学人文社会科学科研基金项目“基于跨界思维的信息咨询新业态研究”(项目编号:115546003)。

摘　　要：[目的]为了实现知识的快速聚类和关联分类,由传统的以资源检索为目标的高校图书馆系统转变为完全面向用户需求的、主动发现和推送知识的图书馆知识发现系统。[过程]本文融合网络爬虫技术和学术资源网站结构化数据的特征,构建了基于随机游走模型,依据摘要词频对文献资料进行主题词的提取、聚类;随后在标签信息标注的基础上,根据相似性对游走过程进行加权处理;最终完成了知识关联分类的知识发现系统。[结果]本文实现了用高效的知识提取手段,基于智慧云、物联网构建更加准确和更具关联性的知识发现系统,提高了高校图书馆知识检索系统的查全率和查准率。[Purpose]In order to realize the fast association classification of knowledge,the traditional university library system with the goal of resource retrieval should transform into a library knowledge discovery system that completely faces the needs of users and actively discovers and pushes knowledge.[Process]In this paper,based on the combination of web crawler technology and the characteristics of structured data of academic resources websites,a random walk model was constructed,and the subject words were extracted and clustered according to the abstract word frequency;then,on the basis of label information tagging,the walking process was weighted according to similarity;Finally,the knowledge discovery system of knowledge association classification was completed.[Result]This paper realized the use of efficient knowledge extraction means to build a more accurate and relevant knowledge discovery system based on the cloud of wisdom and the Internet of things,which improved the recall and precision of the university library knowledge retrieval system.

关 键 词：高校图书馆 摘要信息标注 加权处理 随机游走模型 知识发现系统 

分 类 号：G250.74[文化科学—图书馆学]