Keyphrase Annotation with Graph Co-Ranking

November 07, 2016 ยท Declared Dead ยท ๐Ÿ› International Conference on Computational Linguistics

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Authors Adrien Bougouin, Florian Boudin, Bรฉatrice Daille arXiv ID 1611.02007 Category cs.CL: Computation & Language Citations 14 Venue International Conference on Computational Linguistics Last Checked 4 months ago
Abstract
Keyphrase annotation is the task of identifying textual units that represent the main content of a document. Keyphrase annotation is either carried out by extracting the most important phrases from a document, keyphrase extraction, or by assigning entries from a controlled domain-specific vocabulary, keyphrase assignment. Assignment methods are generally more reliable. They provide better-formed keyphrases, as well as keyphrases that do not occur in the document. But they are often silent on the contrary of extraction methods that do not depend on manually built resources. This paper proposes a new method to perform both keyphrase extraction and keyphrase assignment in an integrated and mutual reinforcing manner. Experiments have been carried out on datasets covering different domains of humanities and social sciences. They show statistically significant improvements compared to both keyphrase extraction and keyphrase assignment state-of-the art methods.
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