TopicRank: Graph-Based Topic Ranking for Keyphrase Extraction

By Adrien Bougouin, Florian Boudin, Béatrice Daille. International Joint Conference on Natural Language Processing, 2013

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Automatic Keyphrase Extraction: A Survey of the State of the Art (2014, background): “…co-occurrence counts (Mihalcea and Tarau, 2004; Matsuo and Ishizuka, 2004) and semantic relatedness (Grineva et al., 2009), and represented the relatedness information collected from a document as a graph (Mihalcea and Tarau, 2004; Wan and Xiao, 2008a; Wan and Xiao, 2008b; Bougouin et al., 2013).”
PositionRank: An Unsupervised Approach to Keyphrase Extraction from Scholarly Documents (2017, methodology): “Several unsupervised approaches leverage word clustering techniques such as ﬁrst grouping candidate words into topics and then, extracting one representative keyphrase from each topic (Liu et al., 2009; Bougouin et al., 2013).”
Keyphrase Generation for Scientific Document Retrieval (2020, background): “A Supplementary material (Witten et al., 1999; Turney, 2003; Nguyen and Kan, 2007; Jiang et al., 2009) and graph-based methods (Mihalcea and Tarau, 2004; Wan and Xiao, 2008; Bougouin et al., 2013; Flo-rescu and Caragea, 2017).”