A Web Service for Author Name Disambiguation in Scholarly Databases

Kunho Kim, Athar Sefid, Bruce A. Weinberg, C. Lee Giles
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引用次数: 18

Abstract

Author Name Disambiguation (AND) is the task of clustering unique author names from publication records in scholarly or related databases. Although AND has been extensively studied and has served as an important preprocessing step for several tasks (e.g. calculating bibliometrics and scientometrics for authors), there are few publicly available tools for disambiguation in large-scale scholarly databases. Furthermore, most of the disambiguated data is embedded within the search engines of the scholarly databases, and existing application programming interfaces (APIs) have limited features and are often unavailable for users for various reasons. This makes it difficult for researchers and developers to use the data for various applications (e.g. author search) or research. Here, we design a novel, web-based, RESTful API for searching disambiguated authors, using the PubMed database as a sample application. We offer two type of queries, attribute-based queries and record-based queries which serve different purposes. Attribute-based queries retrieve authors with the attributes available in the database. We study different search engines to find the most appropriate one for processing attribute-based queries. Record-based queries retrieve authors that are most likely to have written a query publication provided by a user. To accelerate record-based queries, we develop a novel algorithm that has a fast record-to-cluster match. We show that our algorithm can accelerate the query by a factor of 4.01 compared to a baseline naive approach.
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学术数据库中作者姓名消歧的Web服务
作者姓名消歧(AND)是从学术或相关数据库的出版记录中聚类唯一的作者姓名的任务。尽管AND已被广泛研究,并已作为一些任务(例如计算文献计量学和作者科学计量学)的重要预处理步骤,但在大型学术数据库中很少有公开可用的消歧工具。此外,大多数消歧数据都嵌入在学术数据库的搜索引擎中,现有的应用程序编程接口(api)功能有限,并且由于各种原因通常无法为用户所用。这使得研究人员和开发人员很难将这些数据用于各种应用程序(例如作者搜索)或研究。在这里,我们设计了一个新颖的、基于web的RESTful API,用于搜索消除歧义的作者,使用PubMed数据库作为示例应用程序。我们提供两种类型的查询,基于属性的查询和基于记录的查询,它们服务于不同的目的。基于属性的查询检索具有数据库中可用属性的作者。我们研究了不同的搜索引擎,以找到最适合处理基于属性的查询的搜索引擎。基于记录的查询检索最有可能编写用户提供的查询发布的作者。为了加速基于记录的查询,我们开发了一种具有快速记录到集群匹配的新算法。我们表明,与基线朴素方法相比,我们的算法可以将查询速度提高4.01倍。
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