基于粗糙模糊集的智能图书馆文献信息资源检索方法  

Retrieval Method of Document Information Resources in Intelligent Library Based on Rough Fuzzy Set

作　　者：姚玲珍 宋峰雨 YAO Lingzhen;SONG Fengyu(Library,Longyan University,Longyan 364012,China)

机构地区：[1]龙岩学院图书馆,福建龙岩364012

出　　处：《新乡学院学报》2021年第12期48-51,共4页Journal of Xinxiang University

基　　金：龙岩学院青年博士科研启动基金资助项目(LB201810)。

摘　　要：针对传统的图书馆文献信息资源检索方法中存在检索精确度低的问题,提出了基于粗糙模糊集的智能图书馆文献信息资源检索方法。通过分析图书馆文献信息资源的语义信息检测结果,得到了图书馆文献信息资源的粗糙集匹配系数,并构建出了智能图书馆文献信息资源的语义特征分布结构模型;采用空间欠采样技术对文献信息资源分布采样和信息进行了融合处理,提取出文献信息资源的联合相似度特征集,并分析信息资源检索特征;根据分析结果,采用粗糙模糊集特征匹配技术,构建粗糙模度匹配函数,对粗糙模糊集进行聚类分析,结合均值函数检测方法,进行图书馆文献信息资源的优化检索。仿真测试结果表明,采用该方法的图书馆文献信息资源检索精确度较高。Aiming at the problem of low retrieval accuracy for traditional library literature information resource retrieval,a smart library literature information resource retrieval method based on rough fuzzy sets is proposed.Through the semantic information detection results of the library literature information resources,the rough set matching coefficient of the library literature information resources is obtained.Then the semantic feature distribution structure model of the intelligent library literature information resources is constructed.This paper used spatial undersampling technology to sample the distribution of the literature information resources and process integrated information.This paper also extracted the joint similarity feature set of document information resources and analyzed the retrieval features of information resources.According to the analysis results,this paper adopted the rough fuzzy set feature matching technology to construct the rough modulus matching function,clustered the rough fuzzy set,and combined the mean function Detection method to optimize retrieval of library literature information resources.The simulation test results show that the library literature information resource retrieval using this method has high accuracy.

关 键 词：粗糙模糊集 智能图书馆 文献信息 资源检索 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]