知识图谱在领域知识多维分析中的应用途径研究
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摘要
知识图谱为解决众多领域的现实问题提供了新的思想与方法,有助于呈现和分析领域知识及其关联关系。研究工作采用图数据库技术构建领域知识图谱。从简单实体关系和多维复杂关系层面,对知识图谱在领域知识多维分析中的应用途径进行探索。研究表明,知识图谱能够从多维角度组织和分析领域知识与知识关联;灵活地对领域知识及其关系实现可视化呈现;能够方便存储和快速提取知识关系并进行推理。
Knowledge graph provide new ideas and methods for solving realistic problems in many fields, to help reveal and analyze that the domain knowledge and its associated relationships. The research work uses graphic database technology to construct the domain knowledge graph. From the perspective of simple entities relationship and multi-dimensional complex relationships, the application of knowledge graph in multi-dimensional analysis of domain knowledge is explored. The results show that knowledge graph can organize and analyze domain knowledge and knowledge relationship from the point of view of multi-dimension, it also can flexible visualize the domain knowledge and its relationships. Moreover, knowledge graph makes it easy to store and rapidly extract knowledge relationships and do inference researched.
Knowledge graph provide new ideas and methods for solving realistic problems in many fields, to help reveal and analyze that the domain knowledge and its associated relationships. The research work uses graphic database technology to construct the domain knowledge graph. From the perspective of simple entities relationship and multi-dimensional complex relationships, the application of knowledge graph in multi-dimensional analysis of domain knowledge is explored. The results show that knowledge graph can organize and analyze domain knowledge and knowledge relationship from the point of view of multi-dimension, it also can flexible visualize the domain knowledge and its relationships. Moreover, knowledge graph makes it easy to store and rapidly extract knowledge relationships and do inference researched.
引文
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[7]滕广青,毕强.国外本体协调研究前沿进展及热点分析[J].中国图书馆学报,2012,38(1):113-120.
[8]孙雨生,白璧娇.国内基于本体的知识服务研究进展:核心内容[J].图书馆学研究,2018(16):9-16.
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[10]PHAM M C,KLAMMA R,JARKE M.Development of computer science disciplines:A social net work analysis approach[J].Social Network Analysis and Mining,2011,1(4):321-340.
[11]MA F C,LI Y T.Utilisingsocial network analysis to study the characteristics and functions of the co-occurrence network of online tags[J].Online Information Review,2014,38(2):232-247.
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[13]安宁,滕广青,白淑春,等.基于网络Hub的领域核心知识涌现研究[J].图书情报工作,2017,61(18):98-106.
[14]WENG L,MENCZER F.Topicality and impact in social media:Diverse messages,focused messengers[J].PloSONE,2015,10(2):e0118410.
[15]MA Z,LEE Y,YU K H.Ten years of conflict management studies:Themes,concepts and relationships[J].International Journal of Conflict,2008,19(3):234-248.
[16]李纲,李春雅,李翔.基于社会网络分析的科研团队发现研究[J].图书情报工作,2014,58(7):63-70,82.
[17]安宁,滕广青,徐汉青,等.知识群落演化与知识传递模式研究[J].图书馆学研究,2018(21):76-85.
[18]孙雨生,常凯月,朱礼军.大规模知识图谱及其应用研究[J].情报理论与实践,2018,41(11):138-143.
[19]王颖,钱力,谢靖,等.科技大数据知识图谱构建模型与方法研究[J].数据分析与知识发现,2019,3(1):15-26.
[20]徐雷,潘珺.知识网络等相关概念比较分析[J].情报科学,2017,35(12):10-15.
[21]COWIE J,LEHNERT W.Information extraction[J].Communications of the ACM,1996,39(1):80-91.