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Towards Authorship Attribution for Bibliometrics using Stylometric Features
2015
International Conference on Scientometrics and Informetrics
The overwhelming majority of scientific publications are authored by multiple persons; yet, bibliographic metrics are only assigned to individual articles as single entities. In this paper, we aim at a more fine-grained analysis of scientific authorship. We therefore adapt a text segmentation algorithm to identify potential author changes within the main text of a scientific article, which we obtain by using existing PDF extraction techniques. To capture stylistic changes in the text, we adopt
dblp:conf/issi/RexhaKKK15
fatcat:p4xq2fonnfgsfdyks3id4jyxw4