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Journal of Intelligent Information Systems

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02.05.2019

Automatic keyphrase extraction: a survey and trends

verfasst von: Zakariae Alami Merrouni, Bouchra Frikh, Brahim Ouhbi

Erschienen in: Journal of Intelligent Information Systems | Ausgabe 2/2020

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Abstract

Due to the exponential growth of textual data and web sources, an automatic mechanism is required to identify relevant information embedded within them. The utility of Automatic Keyphrase Extraction (AKPE) cannot be overstated, given its widespread adoption in many Information Retrieval (IR), Natural Language Processing (NLP) and Text Mining (TM) applications, and its potential ability to solve difficulties related to extracting valuable information. In recent years, a wide range of AKPE techniques have been proposed. However, they are still impaired by low accuracy rates and moderate performance. This paper provides a comprehensive review of recent research efforts on the AKPE task and its related techniques. More concretely, we highlight the common process of this task, while also illustrating the various approaches used (supervised, unsupervised, and Deep Learning) and released techniques. We investigate the major challenges that such techniques face and depict the specific complexities they address. Besides, we provide a comparison study of the best performing techniques, discuss why some perform better than others and propose recommendations to improve each stage of the AKPE process.

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Titel: Automatic keyphrase extraction: a survey and trends
verfasst von: Zakariae Alami Merrouni
Bouchra Frikh
Brahim Ouhbi
Publikationsdatum: 02.05.2019
Verlag: Springer US
Erschienen in: Journal of Intelligent Information Systems / Ausgabe 2/2020
Print ISSN: 0925-9902
Elektronische ISSN: 1573-7675
DOI: https://doi.org/10.1007/s10844-019-00558-9

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