Deep Learning-Based Text Classification to improve Web Service Discovery

Hadj Madani Meghazi, Sid Ahmed Mostefaoui, Moustafa Maaskri, Youcef Aklouf

Abstract


As more companies and organizations make their business data or resources available on the web through APIs, the number of web APIs has grown substantially. This makes it challenging to locate web APIs quickly and efficiently. To address this issue, service classification has been introduced to simplify the discovery process among a large pool of services. Previous methods have attempted to categorize web services using semantic features, but they have been limited in accuracy. To enhance the discovery of web services, this study proposes a new approach called "DeepLAB-WSC", which focuses on actions extracted from textual descriptions of web services and leverages techniques from deep learning-based text classification. The proposed approach was tested on a real-world web API dataset and produced results that surpass current state-of-the-art works.

Keywords


Service classification; Action extraction; Text classification; Deep learning; Web services discovery

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