New Clustering-Based Semantic Service Selection and User Preferential Model

Web service is the newest development in the contemporary system that transforms the web from a group of information into a disseminated computational device. This article proposes a new web service where the users are given the option to select the service that satisfies the quality of service (QoS) requirements from the set of discovered services. The ultimate aim of this article is to design a clustering-based semantic service selection model (SSSM) and user preferential model (UPM) to enhance the web services. The functional requirements of the service requested are mapped with the discovered services and the nonfunctional requirements are mapped to the QoS parameters of the services retrieved from the universal description, discovery, and integration. The quality attributes have been resolved by using the proposed two-tier user preference model. The Tier-I of the UPM deals with the qualification of the QoS parameters, where the user is presented with the available quality parameters for defining them in the model. The Tier-II of the UPM quantifies the qualified QoS parameters, where the user will set the preference values. Thus, the proposed clustering-based SSM and the UPM have improved the efficiency of the service selection operation, which has been shown using the three critical factors of the service retrieval discernment. The experimental results show the improved precision, recall, and F -measure values of the proposed method.