| 基于RelFinder的图情学科关联数据语义关系发现实践 |
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| 引用本文： | 石泽顺,肖明.基于RelFinder的图情学科关联数据语义关系发现实践[J].图书情报工作,2017,61(17):139-148. |
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| 作者姓名： | 石泽顺 肖明 |
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| 作者单位： | 北京师范大学政府管理学院 北京 100875 |
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| 基金项目： | 本文系2016年度国家社会科学基金项目"基于语义识别的引文分析理论、方法与应用研究"（项目编号：16BTQ073）研究成果之一。 |
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| 摘 要： | 目的/意义]对LISTA数据库收录的图情学科学术文献、期刊、作者的题录数据进行关联数据发布研究，并利用可视化软件RelFinder进行多角度的语义关系发现实验，以期揭示不同学术单元数据之间的隐含关系和一些潜在的规律。方法/过程]首先，选取图情学科为研究领域，抓取LISTA数据库666种期刊、5 075位核心作者以及1 073篇学术文献的题录数据并导入MYSQL数据库。接着，构建轻量级任务本体对数据进行规范化描述，利用开源软件D2RQ转换为RDF三元组，并结合语义仓储软件Virtuoso发布为关联数据。最后，使用RDF可视化软件RelFinder进行图情学科学术单元之间的语义关系发现，对直接关系、一次间接关系、二次间接关系以及多次间接关系的发现过程进行总结。结果/结论]RelFinder能较好地发现图情学科学术文献、期刊、作者之间隐含的深层次关系，对检索学术文献、揭示学术脉络和发现学术领域知识都有重要意义。
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| 关 键 词： | 关联数据 本体 RelFinder 关系发现 |
| 收稿时间： | 2017-03-14 |
The Semantic Relation Discovery Practice of Library and Information Science Linked Data Based on RelFinder |
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| Shi Zeshun,Xiao Ming.The Semantic Relation Discovery Practice of Library and Information Science Linked Data Based on RelFinder[J].Library and Information Service,2017,61(17):139-148. |
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| Authors: | Shi Zeshun Xiao Ming |
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| Institution: | School of Government, Beijing Normal University, Beijing 100875 |
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| Abstract: | Purpose/significance] This paper constructs a study on the linked data sets of academic records of library and information science in the LISTA database which include documents, authors and journals, then makes a semantic relation discovery experiment using RelFinder,to reveal the implicit relations and some potential laws between different academic units.Method/process] First of all, it collects the bibliographic data of 666 LIS journals, 5 075 LIS authors and 1 073 academic papers in LISTA database, and imports them into MYSQL database. Then, a lightweight task-based ontology is used to normalize the data, the open source software D2RQ is to convert the data into RDF triples, and Virtuoso is to publish RDF triples as linked data. Finally, the semantic relation between the library and information science academic units is conducted by the RDF visualization software RelFinder, and the discovery process of direct relationship, indirect relationship, secondary indirect relationship and multiple indirect relationship is summarized.Result/conclusion] RelFinder can reveal the implicit deep relations between academic literature, periodicals and authors. It is of great significance to retrieve academic literature, to reveal the academic framework and to discover the academic knowledge. |
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| Keywords: | linked data ontology RelFinder relation discovery |
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