Service Classification using Deep Learning Models: A Comprehensive Analysis

The process of automatically categorizing services is crucial for identifying, choosing, and integrating services. Lately, in this field the use of algorithms for machine learning has proliferated. While these techniques have shown potential, their evaluation has primarily been on web services datasets that are relatively small and balanced. This restricts their applicability in real-world scenarios. In this study, a novel deep neural network is presented that is capable of automatically converting the simple representations of the service name and description into sophisticated integrated characteristics. This is achieved without the need for feature engineering or restrictions on length. The network is then used to predict the classification of services across 50 different categories. We conducted a comprehensive experiment utilising a dataset of 10,000 real web services to compare the way we approached with five distinct machine learning approaches in order to validate the effectiveness of our strategy. According to the results, our suggested deep neural network model performs better than the others in terms of resilience and classification accuracy.