Logic and Event Based Semantic Relationship Evolution in Service Semantic Link Network

To facilitate reasoning and predicting service evolution relationships with incomplete, partial or uncertain knowledge for supporting an intelligent service application and to preserve the relationship consistency in the whole service networks during Web service evolution processes over time. An approach was presented for event-based relationships evolution detection and reasoning among web services by combining first-order logic and probabilistic graphical models in a single representation. The Web service relationship evolution model was constructed by using available probability information and knowledge based on the related event and their inherent service relationship dependencies. And S-MLN was taken as a logical framework for Web service relationships evolution reasoning with uncertainty to discover and predict evolutionary service relationship classification. The events and evolutionary measures of the research were found to be helpful for evaluating Web service evolution relationships. And it is effective to evaluate the quality of service set classification by SMLN based evolution relationships prediction. The study identifies the theoretical foundations of web service evolution discovery in the context of SLN. This study, based on an established theoretical foundation, will help the research community to gain a deeper understanding of the dynamic relationship in the semantic context of the web services network.