A visual analytics approach to author name disambiguation

Chris W. Muelder, Robert Faris, Kwan-Liu Ma

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Academic publication archives often draw from numerous, heterogeneous sources, whose records can follow differing naming conventions. As such, ambiguity issues concerning authorship of scientific papers often arise, such as authors sharing similar names, the use of first names versus initials, or alternate name spellings for the same author. These ambiguities have plagued research on scientific collaboration and influence. Detecting and correcting these errors is important for maintaining the archive, as well as for ensuring correctness and reliability in any desired subsequent analysis. There are existing analytic methods designed to accomplish this with varying degrees of accuracy, but many of them require fine tuning or manual categorization. We have developed a visual analytics system to interactively control and apply several analytic name disambiguation algorithms in a finely controlled manner and to present the results to the user for verification or correction. We demonstrate the efficacy of our system by using it to find and resolve ambiguities in authorship data collected from Cornell University Library's arXiv.org and the InfoVis 2004 contest dataset with improved accuracy and speed over existing approaches.

Original languageEnglish (US)
Title of host publicationProceedings - 3rd IEEE/ACM International Conference on Big Data Computing, Applications and Technologies, BDCAT 2016
PublisherAssociation for Computing Machinery, Inc
Pages52-60
Number of pages9
ISBN (Electronic)9781450346177
DOIs
StatePublished - Dec 6 2016
Event3rd IEEE/ACM International Conference on Big Data Computing, Applications and Technologies, BDCAT 2016 - Shanghai, China
Duration: Dec 6 2016Dec 9 2016

Other

Other3rd IEEE/ACM International Conference on Big Data Computing, Applications and Technologies, BDCAT 2016
CountryChina
CityShanghai
Period12/6/1612/9/16

Keywords

  • Bibliographies
  • Coauthor graphs
  • Name ambiguity
  • Visual analytics

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems

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  • Cite this

    Muelder, C. W., Faris, R., & Ma, K-L. (2016). A visual analytics approach to author name disambiguation. In Proceedings - 3rd IEEE/ACM International Conference on Big Data Computing, Applications and Technologies, BDCAT 2016 (pp. 52-60). Association for Computing Machinery, Inc. https://doi.org/10.1145/3006299.3006302