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作 者:只莹莹[1] ZHI Yingying(National Library of China,Beijing 100081,China)
机构地区:[1]国家图书馆,北京100081
出 处:《农业图书情报学刊》2018年第7期47-50,共4页Journal of Library and Information Sciences in Agriculture
摘 要:随着数字资源数量的快速成倍增长,用户对个性和深层的知识发现服务需求日益增加,以及机器学习技术的又一次空前繁荣,让图书馆人看到了利用机器学习技术提升知识发现系统的美好前景。文章简要介绍了一下机器学习技术和图书馆发现系统的现状,分析了机器学习技术应用于图书馆知识发现系统中的必然性。最后以基于知识图谱的发现工具Yewno为例,展示了以概念和联系为核心的、发掘知识内在深层次联系的可视化知识网络。With the rapid growth of digital resource, and the increasing demands on individual and deep knowledge discovery service, as well as the unprecedented prosperity of machine learning, the librarians see a bright future for using machine learning technology to improve library discover. This paper introduced machine learning technology and current situation of library discover briefly, analyzed the necessity of applying machine learning technology in library discover, and finally took Yewno, a discovery tool based on knowledge graph, as the example, to reveal a visual knowledge network with the conception and relation as the core and the exploration of deep connection of knowledge.
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