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文献数据库中作者名消歧算法研究 被引量：7

Research on Author Name Disambiguation Algorithm in the Literature Database
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摘要 在深入分析基于图的人名识别框架GHOST的基础上,针对其存在的局限性,结合对文献信息的文本挖掘提出一种更适用于文献数据库的作者名消歧算法,并从中选取标题以及出版物名称这两个特征进行实证研究,该算法在准确率、召回率等指标方面都有良好的表现,F1平均值达到84%,具备较好的消歧效果。 This paper firstly analyzes a graphical fi＇amework for name disambiguation called GHOST, and then provides a modified name disambiguation algorithm combining with the text mining of literature information. The new algorithm is more suitable for literature database, making up for the limitations existed in GHOST. Based on selecting title and publication name as computing feature from the literature information, the experiment shows that the algorithm achieves high precision and recall value, and F1 reaches 84% , which is good enough for name disambiguation.
作者 郭舒
机构地区 中国科学院国家科学图书馆 中国科学院大学
出处 《现代图书情报技术》 CSSCI 北大核心 2013年第7期69-74,共6页 New Technology of Library and Information Service
关键词 作者名消歧 GHOST 文本挖掘 消歧算法 Author name disambiguation GHOST Text mining Disambiguation algorithm
分类号 TP391.1 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献13

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二级参考文献14

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共引文献9

同被引文献93

  • 1余传明,钟韵辞,林奥琛,安璐.基于网络表示学习的作者重名消歧研究[J].数据分析与知识发现,2020,4(2):48-59. 被引量：10
  • 2曹犟,邬晓钧,夏云庆,郑方.基于拼音索引的中文模糊匹配算法[J].清华大学学报（自然科学版）,2009(S1):1328-1332. 被引量：14
  • 3曹雷.面向专利战略的专利信息分析研究[J].科技管理研究,2005,25(3):97-100. 被引量：60
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引证文献7

二级引证文献29

现代图书情报技术
2013年 第7期

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