Web Based Composition using Machine Learning Approaches: A Literature Review

Abstract

Web Service Composition technology involves the integration of various atomic web services to perform huge scale tasks. As the number of web services is continuously growing, the need for composite web services also increases simultaneously. Since 2000, academic and systematic research has significantly focused on Web-Based Composition (WBC) in many well-reputed scientific journals and presented insight on several issues related to semantic Web and machine learning. In this paper, we present a review on the main contributions related to WBC using Machine Learning approaches. Our analysis and evaluation of those papers give a remarkable insight into the different approaches and planning models with strategies that were developed by researchers and IT professionals. This literature review paper intends to give researchers, interested in WBC, a valuable source of information and also fast-track their researches towards future technologies related to artificial intelligence and machine learning in WBC. The related work onto WBC, its application, research gap, the current status of WBC, and future challenges are also discussed.