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AuthCrowd: Author Name Disambiguation and Entity Matching using Crowdsourcing

Antonio, Correia and Diogo, Guimaraes and Dennis, Paulino and Jameel, Mohammad Shoaib and Daniel, Schneider and Benjamin, Fonseca and Hugo, Paredes (2021) AuthCrowd: Author Name Disambiguation and Entity Matching using Crowdsourcing. In: International Conference on Computer Supported Cooperative Work in Design, 2021-05-05 - 2021-05-07, Online. (In Press)

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Abstract

Despite decades of research and development in named entity resolution, dealing with name ambiguity is still a a challenging issue for much bibliometric-enhanced information retrieval (IR) tasks. As new bibliographic datasets are created as a result of the upward growth of publication records worldwide, more problems arise when considering the effects of errors resulting from missing data fields, duplicate entities, misspellings, extra characters, etc. As these concerns tend to be of large-scale, both the general consistency and the quality of electronic data are largely affected. This paper presents an approach to handle these name ambiguity problems through the use of crowdsourcing as a complementary means to traditional unsupervised approaches. To this end, we present “AuthCrowd”, a crowdsourcing system with the ability to decompose named entity disambiguation and entity matching tasks. Experimental results on a real-world dataset of publicly available papers published in peer-reviewed venues demonstrate the potential of our proposed approach for improving author name disambiguation. The findings further highlight the importance of adopting hybrid crowd-algorithm collaboration strategies, especially for handling complexity and quantifying bias when working with large amounts of data.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: _not provided_
Uncontrolled Keywords: bibliometrics; citation analysis; CSCWD; degree of collaboration; evaluation; science of science; scientometrics
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 17 Mar 2021 08:30
Last Modified: 12 May 2021 12:14
URI: http://repository.essex.ac.uk/id/eprint/30049

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