Abstract
Author name ambiguity in a digital library may affect the findings of research that mines authorship data of the library. This study evaluates author name disambiguation in DBLP, a widely used but insufficiently evaluated digital library for its disambiguation performance. In doing so, this study takes a triangulation approach that author name disambiguation for a digital library can be better evaluated when its performance is assessed on multiple labeled datasets with comparison to baselines. Tested on three types of labeled data containing 5000 to 6 M disambiguated names, DBLP is shown to assign author names quite accurately to distinct authors, resulting in pairwise precision, recall, and F1 measures around 0.90 or above overall. DBLP’s author name disambiguation performs well even on large ambiguous name blocks but deficiently on distinguishing authors with the same names. Compared to other disambiguation algorithms, DBLP’s disambiguation performance is quite competitive, possibly due to its hybrid disambiguation approach combining algorithmic disambiguation and manual error correction. A discussion follows on strengths and weaknesses of labeled datasets used in this study for future efforts to evaluate author name disambiguation on a digital library scale.
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27 November 2018
In the original publication of the article, in Abstract, the size of labeled data was incorrectly reported.
27 November 2018
In the original publication of the article, in Abstract, the size of labeled data was incorrectly reported.
Notes
DBLP-related papers were searched using the term “DBLP” with a Document Type filter (“Conference Paper and Article”) at https://www.scopus.com/search/form.uri?display=basic.
At the time of this study, the service is provided by Clarivate Analytics at https://clarivate.com/hcr/.
The dataset in a XML format can be downloaded from dblp.org/xml/release/dblp-2017-09-03.xml.gz.
DBLP team kindly provided the list of 39,152 name pairs in synonym relation for this study.
For details, see http://dblp.org/faq/17334571.
Splitting can affect the pP by decreasing the denominator in Eq. (1) but also by decreasing the numerator, thus reducing the overall impact of splitting on pP.
For comparison, decimal points of performance results in Table 4 were modified to be consistent with metric units in other studies. Also, B-Cubed metrics were calculated for QIAN on all names regardless of block size, following the referenced study.
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Acknowledgements
I would like to thank Florian Reitz (Leibniz Center for Informatics, Schloss Dagstuhl, Germany) for providing the list of synonyms in DBLP and Alan Filipe Santana (Departamento de Ciência da Computação, Universidade Federal de Minas Gerais, Brazil) for sharing the raw KISTI dataset. I am also thankful to anonymous reviewers for their comments. This work was supported by grants from the National Science Foundation (Grants #1561687 and #1535370), the Alfred P. Sloan Foundation, and the Ewing Marion Kauffman Foundation.
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Kim, J. Evaluating author name disambiguation for digital libraries: a case of DBLP. Scientometrics 116, 1867–1886 (2018). https://doi.org/10.1007/s11192-018-2824-5
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DOI: https://doi.org/10.1007/s11192-018-2824-5
Keywords
- Author name disambiguation
- Digital library
- Triangulation
- Disambiguation evaluation
- DBLP