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A survey of author name disambiguation techniques: 2010–2016

Published online by Cambridge University Press:  05 December 2017

Ijaz Hussain Open the ORCID record for Ijaz Hussain [Opens in a new window]  and
Sohail Asghar
Ijaz Hussain
Affiliation:
Department of Computer Science, COMSATS Institute of Information Technology, Islamabad 45550, Pakistan e-mail: [email protected], [email protected]
Sohail Asghar
Affiliation:
Department of Computer Science, COMSATS Institute of Information Technology, Islamabad 45550, Pakistan e-mail: [email protected], [email protected]
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Abstract

Digital libraries content and quality of services are badly affected by the author name ambiguity problem in the citations and it is considered as one of the hardest problems faced by the digital library researchers. Several techniques have been proposed in the literature for the author name ambiguity problem. In this paper, we reviewed some recently presented author name disambiguation techniques and give some challenges and future research directions. We analyze the recent advancements in this field and classify these techniques into supervised, unsupervised, semi-supervised, graph-based and heuristic-based techniques according to their problem formulation that is mainly used for the author name disambiguation. A few surveys have been conducted to review different techniques for the author name disambiguation. These surveys highlighted only the methodology adopted for author name disambiguation but did not critically review their shortcomings. This survey provides a detailed review of author name disambiguation techniques available in the literature, makes a comparison of these techniques at an abstract level and discusses their limitations.

Type
Adaptive and Learning Agents
Information
The Knowledge Engineering Review , Volume 32 , 2017 , e22
Copyright
© Cambridge University Press, 2017 

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