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A Comparison of Centrality Measures for Graph-Based Keyphrase Extraction

Florian Boudin 1, *
* Corresponding author
1 TALN
LINA - Laboratoire d'Informatique de Nantes Atlantique
Abstract : In this paper, we present and compare various centrality measures for graph-based keyphrase extraction. Through experiments carried out on three standard datasets of different languages and domains, we show that simple degree centrality achieve results comparable to the widely used TextRank algorithm, and that closeness centrality obtains the best results on short documents.
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Submitted on : Monday, August 5, 2013 - 2:43:42 PM
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Florian Boudin. A Comparison of Centrality Measures for Graph-Based Keyphrase Extraction. International Joint Conference on Natural Language Processing (IJCNLP), Oct 2013, Nagoya, Japan. pp.834-838. ⟨hal-00850187⟩

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