Service Composition and Customization of Its Features based on Combined Classification

By promoting service-oriented architecture in e-services of organizations and inter-organizational relationships, service quality is more focused. To provide high quality combined service, it is necessary to identify quality requirements of users and offer service in line with those. Service users tend to choose a combined service among the huge collection of available services based on quality of service. In the case of competition among rivals, service providers must customize features of service as one of the key strategies. Customization involves the combination of service features based on user requests, these strategies raise new problems on the expression and dissemination of quality information, service identification and setting qualitative offers to service users. In the previous methods, pre-processing step was not performed in the services set, and false service suggestions to the user were possible.  In this study, nearest neighbor algorithm was offered to identify consumers and customize their quality of service. Also, Isodata has been used to cluster and filter the services. At the end, a case study was presented to illustrate the proposed method. The results of the evaluation show that the proposed method has tried to solve the existing shortcomings.

Service Composition and Customization of Its Features based on Combined Classification Keywords:

Service Selection , Access Control Based on the Features , Service Quality Model , Customization of Services Features , Service composition , Web Services , Clustering , Optimization , Isodata Clustering , k-Means Algorithm