Using Noun Phrase Heads to Extract Document Keyphrases

By Ken Barker, Nadia Cornacchia. Canadian Conference on AI, 2000

298 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/26324601f7c25430adbbeec931b28cf11b2dbe81

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In Artificial Intelligence

Citations in the corpus

Improved Automatic Keyword Extraction Given More Linguistic Knowledge (2003, background): “For example, Barker and Cornacchia (2000) discuss an al-gorithm where the number of words and the frequency of a noun phrase, as well as the frequency of the head noun is used to determine what terms are keywords.”
Single Document Keyphrase Extraction Using Neighborhood Knowledge (2008, background): “Barker and Cornacchia (2000) propose a simple system for choosing noun phrases from a document as keyphrases.”
SemEval-2010 Task 5 : Automatic Keyphrase Extraction from Scientific Articles (2010, methodology): “…new systems and techniques for the task (Frank et al., 1999; Witten et al., 1999; Turney, 1999; Hulth, 2003; Turney, 2003; Park et al., 2004; Barker and Corrnacchia, 2000; Hulth, 2004; Matsuo and Ishizuka, 2004; Mihalcea and Tarau, 2004; Medelyan and Witten, 2006; Nguyen and Kan, 2007; Wan…”
PositionRank: An Unsupervised Approach to Keyphrase Extraction from Scholarly Documents (2017, methodology): “In unsupervised approaches, various measures such as tf-idf and topic proportions are used to score words, which are later aggregated to obtain scores for phrases (Barker and Cornacchia, 2000; Zhang et al., 2007; Liu et al., 2009).”
Automatic Keyphrase Extraction: A Survey of the State of the Art (2014, background): “…in Wikipedia article titles to be candidates (Grineva et al., 2009), and (4) extracting n-grams (Witten et al., 1999; Hulth, 2003; Medelyan et al., 2009) or noun phrases (Barker and Cornacchia, 2000; Wu et al., 2005) that satisfy pre-deﬁned lexico-syntactic pattern(s) (Nguyen and Phan, 2009).”
Keyphrase Extraction in Scientific Publications (2007, methodology): “These features captured candidate length and frequency like Barker and Cornacchia’s system, but additionally modele the candidate’s position within the document.”