Affiliations: [a] Centro de Aplicaciones de Tecnologías de Avanzada, Playa, La Habana, Cuba | [b] Universidad Tecnológica de La Habana José Antonio Echeverría, Marianao, La Habana, Cuba | [c] Universidad de Castilla-La Mancha, Paseo de La Universidad, Ciudad Real, Spain
Correspondence:
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Corresponding author: Yamel Pérez-Guadarramas, Centro de Aplicaciones de Tecnologías de Avanzada, 7ma A, No. 21406, e/214 y 216, Playa, La Habana, Cuba. E-mail: [email protected].
Abstract: Automatic keyphrase extraction from texts is useful for many computational systems in the fields of natural language processing and text mining. Although a number of solutions to this problem have been described, semantic analysis is one of the least exploited linguistic features in the most widely-known proposals, causing the results obtained to have low accuracy and performance rates. This paper presents an unsupervised method for keyphrase extraction, based on the use of lexico-syntactic patterns for extracting information from texts, and a fuzzy topic modeling. An OWA operator combining several semantic measures was applied to the topic modeling process. This new approach was evaluated with Inspec and 500N-KPCrowd datasets. Several approaches within our proposal were evaluated against each other. A statistical analysis was performed to substantiate the best approach of the proposal. This best approach was also compared with other reported systems, giving promising results.
