Evaluation of Features for Author Name Disambiguation Using Linear Support Vector Machines
Dendek, Piotr Jan
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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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