With the advent of more users accessing internet for information retrieval, researchers are more focused in creating system for recommendation of web service(WS) which minimize the complexity of selection process and optimize the quality of recommendation. This paper implements a framework for recommendation of personalized WS coupled with the quality optimization, using the quality features available in WS Ontology. It helps users to acquire the best recommendation by consuming the contextual information and the quality of WS. Adaptive framework performs i) the retrieval of context information ii) calculation of similarity between users preferences and WS features, similarity between preferred WS with other WS specifications iii) collaboration of web service ratings provided by current user and other users. Finally, WS quality features are considered for computing the Quality of Service. The turnout of recommendation reveals the selection of highly reliable web services, as credibility is used for QoS predication.
S. Subbulakshmi, Ramar, K., Renjitha, R., and Sreedevi, T. U., “Implementation of Adaptive Framework and WS Ontology for Improving QoS in Recommendation of WS”, in The International Symposium on Intelligent Systems Technologies and Applications, Intelligent Systems Technologies and Applications 2016, Cham, 2016.