图书情报工作 ›› 2014, Vol. 58 ›› Issue (23): 143-148,142.DOI: 10.13266/j.issn.0252-3116.2014.23.022

• 知识组织 • 上一篇    

中文文献题录数据作者重名消解问题研究

朱云霞   

  1. 南京邮电大学计算机学院
  • 收稿日期:2014-10-11 修回日期:2014-11-20 出版日期:2014-12-05 发布日期:2014-12-05
  • 作者简介:朱云霞, 南京邮电大学计算机学院副教授, E-mail:zhuyx@njupt.edu.cn.
  • 基金资助:

    本文系教育部人文社会科学青年基金项目"复杂网络视角下的科学共同体研究"(项目编号:14YJC870028)和南京邮电大学校级一般科研项目"基于复杂网络的科学共同体知识发现"(项目编号:NY213059)研究成果之一.

Study on Author Name Disambiguation for Chinese Bibliographic Information

Zhu Yunxia   

  1. School of Computer Science & Technology, Nanjing University of Posts and Telecommunications, Nanjing 210023
  • Received:2014-10-11 Revised:2014-11-20 Online:2014-12-05 Published:2014-12-05

摘要:

在对目前各种作者重名消解方法进行总结的基础上, 针对中文文献题录数据特征, 将重名消解问题转换为同名作者文献的分类问题, 提出一种基于规则和相似度的重名消解框架模型, 并对其中的分解规则和合并规则进行详细的算法描述, 最后选取3个学科的重名作者数据集进行实验, 实验结果表明该模型能有效提高作者重名消解的准确率.

关键词: 重名消解, 相似度, 规则, 算法

Abstract:

In view of the characteristics of the Chinese bibliographic information, this paper summarized the current name disambiguation methods, proposed a model based on rules and the similarity, and thus converted the author name disambiguation problems to the literature classification problems. Specific decomposition and merger rules and corresponding algorithm had been described in detail. Finally some same-named bibliographic information of the three disciplines were selected as the experimental data sets, the results showed that this model can effectively improve the correct of name disambiguation.

Key words: name disambiguation, similarity, rules, algorithm

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