Personalized Web Services Composition Using Artificial Intelligence

Abstract The process of creating new services by integrating existing ones is known as service composition. It is regarded as one of the most difficult tasks in a distributed and dynamic setting. In general, the composition process entails looking for existing services in a certain domain, selecting the suitable service, coordinating composition flow, and activating services. Researchers have been studying the need of web service composition using artificial intelligence extensively over the last few years. As a result, numerous solutions and novel approaches to addressing this issue are given. Our goal in this research is to use artificial intelligence to personalize web services composition. In our case, We employed natural language processing (NLP) to examine the descriptions and functionality of existing online services. Based on the user profile, AI algorithms can recommend and select appropriate services that meet the user’s needs. The experimental study shows that the proposed model can achieve robust results. In fact, our solution achieves 99.45% accuracy and 99.74% Precision.