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Applying OWA Operator in the Semantic Processing for Automatic Keyphrase Extraction

  • Manuel Barreiro-Guerrero
  • Alfredo Simón-CuevasEmail author
  • Yamel Pérez-Guadarrama
  • Francisco P. Romero
  • José A. Olivas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11896)

Abstract

The automatic keyphrases extraction from texts is a useful task for many computational systems in the natural language processing and text mining fields. Although several solutions to this problem have been developed, the semantic analysis has been one of the linguistic features less exploited in the most reported proposal, causing that the obtained results still show low accuracy and performance rates. This paper presents an unsupervised method for keyphrase extraction, which is based on the use of lexical-syntactic patterns for extracting information from texts and a fuzzy modelling of topics. An OWA operator which combines several semantics measures has been applied in the topic modelling process. This new approach was evaluated with Inspec and 500N-KPCrowd datasets and compared with other reported systems, obtaining promising results.

Keywords

Automatic keyphrase extraction Linguistic patterns Topic modelling Semantic processing OWA operator 

Notes

Acknowledgments

This work has been partially supported by FEDER and the State Research Agency (AEI) of the Spanish Ministry of Economy and Competition under grant MERINET: TIN2016-76843-C4-2-R (AEI/FEDER, UE).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Universidad Tecnológica de La Habana José Antonio EcheverríaMarianaoCuba
  2. 2.Centro de Aplicaciones de Tecnologías de Avanzada (CENATAV)PlayaCuba
  3. 3.Universidad de Castilla-La ManchaCiudad RealSpain

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