A comparison of centrality measures for graph-based keyphrase extraction

In this paper, we present and compare various centrality measures for graph-based keyphrase extraction. Through ex-periments carried out on three standard datasets of different languages and do-mains, we show that simple degree cen-trality achieve results comparable to the widely used TextRank algorithm, and that closeness centrality obtains the best results on short documents.