Evaluation of Features for Author Name Disambiguation Using Linear Support Vector Machines

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Authors
Dendek, Piotr Jan
Bolikowski, Łukasz
Łukasik, Michał
Date
2012-03-27
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Publisher
IEEE Computer Society Conference Publishing Services
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Abstract
Author name disambiguation allows to distinguish between two or more authors sharing the same name. In a previous paper, we have proposed a name disambiguation framework in which for each author name in each article we build a context consisting of classification codes, bibliographic references, co-authors, etc. Then, by pairwise comparison of contexts, we have been grouping contributions likely referring to the same people. In this paper we examine which elements of the context are most effective in author name disambiguation. We employ linear Support Vector Machines (SVM) to find the most influential features.
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Keywords
computer science    information retrieval    linearity    bibliographies    context    supervised learning    classification algorithms    support vector machines    name disambiguation
Citation
P. J. Dendek, Ł. Bolikowski, M. Łukasik. Evaluation of Features for Author Name Disambiguation Using Linear Support Vector Machines. In:. Proceedings of the 10th IAPR International Workshop on Document Analysis Systems. 2012; p. 440-444.
URI
http://depot.ceon.pl/handle/123456789/1973
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Materiały konferencyjne ICM / ICM Conference Papers