MACHINE LEARNING IN EFFICIENT AND EFFECTIVE WEB SERVICE DISCOVERY

Authors

  • KAILASH CHANDER BHARDWAJ Department of Computer Science and Engineering Thapar University, Patiala- 147004, India
  • R.K. SHARMA School of Mathematics and Computer Applications Thapar University, Patiala-147004. India
  • R.K. SHARMA School of Mathematics and Computer Applications Thapar University, Patiala-147004. India

Keywords:

Semantics, web ontology language, web service description language, web services modeling language, web service modeling ontology, neural networks, fuzzy logic, ontology, quality of services

Abstract

The web service discovery mechanism has continuously evolved during the last years. There is plethora of information available about various techniques and methods used for meeting the challenge of improving web service discovery. A tremendous effort has been reported in literature and researchers are still contributing to make the web service discovery more effective and efficient. This paper discusses various eminent researchers’ work in this direction using machine learning based techniques. Machine learning is a promising area for researchers to produce accurate estimates consistently. Machine learning system effectively “learns” how to estimate from training set of completed projects. We hope that this paper would benefit researchers to carry further work discussed in this paper and provide an outlook for the future research trends.

 

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2015-03-15

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