Novel Clustering-Based Web Service Recommendation Framework

Alok Jagadev, Priya Pandharbale, Sachi Mohanty

OAI: oai:igi-global.com:285015 • DOI: 10.4018/IJSDA.20220901.oa1

Normally web services are classified originate in on the quality of service, wherever the term quality is not absolute and it is a relative term. The quality of web services is measured or derived using various parameters like reliability, scalability, flexibility, availability, etc. However, the limitation of these methods is that they are producing similar web services in recommendation lists some times. To address this research problem, the novel improved the Clustering-based web service recommendation method is proposed in this project. This approach is mainly dealing to produce diversity in the results of web service recommendation. In this method, functional interest, QoS preference, and diversity features are combined to produce the unique recommendation list of web services to end-users. To produce the unique recommendation results, we proposed a vary web service classify order that is clustering-based on web services' functional relevance such as non-useful pertinence, recorded client intrigue importance, potential client intrigue significance, etc.

Adaptive & Complex Systems Computer Science and Information Technology Computer Engineering