使用K-way谱聚类方法在作者引文中消除姓名歧义

Hui Han, H. Zha, C. Lee Giles
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引用次数: 308

摘要

一个作者可能有多个名字,多个作者可能仅仅因为名字缩写、相同的名字或出版物或参考书目(引文)中的名字拼写错误而共享同一个名字。这可能会产生名称歧义,从而影响文档检索、web搜索和数据库集成的性能,并可能导致信用归属不当。本文提出了一种使用K-way谱聚类的无监督学习方法,该方法可以消除引文中作者的歧义。该方法利用三种类型的引用属性:合著者姓名、论文标题和出版地点标题。该方法以从DBLP数据库书目和作者主页收集的16个名称数据集为例进行了说明,并表明使用这些引文属性可以实现名称消歧
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Name disambiguation in author citations using a K-way spectral clustering method
An author may have multiple names and multiple authors may share the same name simply due to name abbreviations, identical names, or name misspellings in publications or bibliographies (citations). This can produce name ambiguity which can affect the performance of document retrieval, web search, and database integration, and may cause improper attribution of credit. Proposed here is an unsupervised learning approach using K-way spectral clustering that disambiguates authors in citations. The approach utilizes three types of citation attributes: co-author names, paper titles, and publication venue titles. The approach is illustrated with 16 name datasets with citations collected from the DBLP database bibliography and author home pages and shows that name disambiguation can be achieved using these citation attributes
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