Keyphrase Extraction in Scientific Publications

By Thuy Dung Nguyen, Min-Yen Kan. International Conference on Asian Digital Libraries, 2007

410 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Single Document Keyphrase Extraction Using Neighborhood Knowledge (2008, background): “Nguyen and Kan (2007) focus on keyphrase extraction in scientific publications by using new features that capture salient morphological phenomena found in scientific keyphrases.”
SemEval-2010 Task 5 : Automatic Keyphrase Extraction from Scientific Articles (2010, methodology): “Nguyen and Kan (2007) collected a dataset containing 120 computer science articles, ranging in length from 4 to 12 pages.”
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).”
Automatic Keyphrase Extraction via Topic Decomposition (2010, methodology): “Automatic keyphrase extraction is widely used in information retrieval and digital library (Turney, 2000; Nguyen and Kan, 2007).”
PositionRank: An Unsupervised Approach to Keyphrase Extraction from Scholarly Documents (2017, methodology): “The third dataset was made available by Nguyen and Kan (2007) and consist of research papers from various disciplines.”
Deep Keyphrase Generation (2017, methodology): “Since the NUS dataset did not speciﬁcally mention the ways of splitting training and testing data, the results of the supervised baseline models are obtained through a ﬁve-fold cross-validation.”