摘要
文章通过对CLOD、KIELD等关联数据相关会议、谷歌学术、IEEE和Springer等数据库基于关联数据的知识发现技术文献的调研与整理,分析和总结了基于关联数据的知识发现技术发展现状和发展趋势。研究认为:根据对关联数据的挖掘层次的不同,将检索结果分为间接挖掘、直接挖掘和链接挖掘三类;总体而言,基于关联数据的知识发现研究仍处于探索阶段,相关研究较少且缺乏统一框架;基于关联数据的知识发现统一框架的构建以及针对关联数据知识发现技术的完善将是未来研究的重点。
This paper discusses the current status and future directions of the related studies of knowledge discovery technology based on linked data。 By Using IEEE,Springer,Google Scholar and other scholarly search engines and collects papers about this subject from related conferences,such as COLD and KIELD,this paper makes a comprehensive study in this subject of research and classifies related papers according to the different knowledge discovery methods. In general,knowledge discovery based on linked data is still in the exploratory stage. There still exists some problems in the knowledge discovery based on linked data, such as the quality problem of linked data;and there is no unified framework for those methods. Getting more convenient knowledge discovery methods based on linked data and building a unified framework for them will be the focus of future research.
出处
《图书与情报》
CSSCI
北大核心
2016年第5期119-125,136,共8页
Library & Information
关键词
关联数据
知识发现
述评
linked data
knowledge discovery
review
