In this paper, we present and compare various centrality measures for graphbased 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.
Boudin REF compare various centrality measures for graph-based keyphrase extraction.
A Comparison of Centrality Measures for Graph-Based Keyphrase Extraction
IJCNLP
Computer Science