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Computación y Sistemas
versión On-line ISSN 2007-9737versión impresa ISSN 1405-5546
Resumen
MEGHAZI, Hadj Madani; MOSTEFAOUI, Sid Ahmed; MAASKRI, Moustafa y AKLOUF, Youcef. Deep Learning-Based Text Classification to Improve Web Service Discovery. Comp. y Sist. [online]. 2024, vol.28, n.2, pp.529-542. Epub 31-Oct-2024. ISSN 2007-9737. https://doi.org/10.13053/cys-28-2-4556.
Due to the rising number of firms and organizations offering access to their business data or resources on the internet through APIs, there has been a significant increase in the number of web APIs. This poses a difficulty in swiftly and effectively finding online APIs. In order to tackle this problem, the introduction of service classification has been implemented to streamline the process of finding services within a vast array of options. Prior approaches have endeavored to classify web services based on semantic characteristics, although their precision has been constrained. This work introduces a novel strategy named “DeepLAB-WSC” to improve the identification of web services. The approach specifically emphasizes actions derived from textual descriptions of web services and utilizes advanced techniques from deep learning-based text classification. The suggested methodology was evaluated using a real-world web API dataset and achieved superior results compared to existing state-of-the-art research.
Palabras llave : Service classification; action extraction; text classification; deep learning; web services discovery.












