An AIS-Based Service Match Model

Aiming at the problem that self-learning ability of the current system usually appears weak during service discovery, a novel artificial immune system (AIS) based service match model is proposed, which is based on the reference to the principles of cellpsilas mutation, evaluation and the quadratic response abilities, as well as simulation on the antibody-antigen identification mechanism. Theoretical analysis and simulations both show that the model can not only increasing the recall ratio and matching speed, but also realizing the function that deriving similar service request from known service request and then searching the best matching service. Furthermore, this service matching model is able to improve systempsilas adaptive learning, memorizing and dynamic evaluating abilities in service matching process.