Abstract
While automatic keyphrase extraction has been examined extensively, state-of-theart performance on this task is still much lower than that on many core natural language processing tasks. We present a survey of the state of the art in automatic keyphrase extraction, examining the major sources of errors made by existing systems and discussing the challenges ahead. © 2014 Association for Computational Linguistics.
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CITATION STYLE
Hasan, K. S., & Ng, V. (2014). Automatic keyphrase extraction: A survey of the state of the art. In 52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014 - Proceedings of the Conference (Vol. 1, pp. 1262–1273). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/p14-1119
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