基于Lingo3G聚类算法的机构知识库跨库知识整合与知识指纹服务实现  

Cross-database Knowledge Integration and Fingerprint of Institutional Repositories with Lingo3G Clustering Algorithm

作　　者：卢利农 祝忠明 张旺强 王小春 Lu Linong;Zhu Zhongming;Zhang Wangqiang;Wang Xiaochun(Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou 730000,China;CASWIZ Information Consulting Co.,Ltd.,Lanzhou 730000,China)

机构地区：[1]中国科学院西北生态环境资源研究院,兰州730000 [2]兰州中科维智信息咨询有限公司,兰州730000

出　　处：《数据分析与知识发现》2021年第5期127-132,共6页Data Analysis and Knowledge Discovery

摘　　要：【目的】基于主题跨库检索服务相关研究成果,集成优化Lingo3G算法并结合Solr打分规则,实现机构知识库的跨库知识整合和知识指纹服务。【方法】分析用户的实际需求,构建知识整合分析与可视化功能框架,选择其中关键的技术和方法搭建平台,探索知识整合的可行性。【结果】在机构知识库中研究计算知识指纹特征,以可视化的形式组织呈现知识指纹图谱,聚类实现与第三方数据库的跨库知识整合服务。【局限】由于跨库检索的数据库结构和设计方法各不相同且很多数据库没有公开资源检索接口,还无法普遍解决跨库检索的局限性。【结论】基于Lingo3G聚类算法的创新集成,可为机构知识库跨库检索提供一套有效的提高知识资源整合、挖掘知识服务能力的功能体系。[Objective] This study optimizes the Lingo3 G algorithm with the help Solr scoring rules, aiming to realize the cross-database knowledge integration and knowledge fingerprint services of the institutional repository.[Methods] First, we analyzed user needs, and constructed a functional framework for knowledge integration analysis and visualization. Then, we selected key technologies and methods to build a platform, and explored the feasibility of knowledge integration. [Results] The proposed method calculated the characteristics of knowledge fingerprints in the institutional knowledge base. It organized and visualized knowledge fingerprints, as well as integrated cross-database knowledge through clustering. [Limitations] Due to the differences of database structure and cross-database retrieval methods( i.e., no public resource API), we did not address all limits of crossdatabase retrieval. [Conclusions] The proposed method could help institutional knowledge repositories effectively integrate their knowledge resources and improve service capabilities.

关 键 词：机构知识库 聚类算法 知识整合 知识指纹 跨库检索 Lingo3G 

分 类 号：G354[文化科学—情报学]