Layer-based Composite Reputation Bootstrapping

We propose a novel generic reputation bootstrapping framework for composite services. Multiple reputation-related indicators are considered in layer-based to implicitly reflect the of component The importance an indicator on future performance service is learned using modified Random Forest algorithm. topology-aware Deep Neural Network (fDNN) find correlations between and trained fDNN model predicts new with confidence value. Experimental results real-world dataset prove efficiency proposed approach.