A New Web Service Evaluation Model with Fuzzy C-Means Artificial Immune Network Memory Classifier

In this paper a new evaluation model is proposed which supports to customize evaluation attributes dynamically instead of standardized evaluation attributes Through expanding the OWL-S ontology a Web service ontology is constructed. Based on fuzzy theory and artificial immune network, a new data classification method, named fuzzy C-Means artificial immune network memory classifier (FCMAINMC), is put forward. According the algorithm, memory antibody collection in which characteristics of service are condensed is abstracted, and each service (antigen) that belongs to some type is also obtained. Using membership matrix and a hundred-mark way, evaluation result which reflects Web quality of service is obtained. The prototype is designed. It is applied to case evaluation fruitfully, and the experiment results are veracious and reliable as well as stable.