Adaptive Services Selection Method Research in AmI Environment
Shufeng Wang · Journal of Chinese Computer Systems · 2011
Due to the fast increase of the available web services and the difference of the users′ preferences,it is difficult to select a suitable service for a user in the AmI environment in adaptive way.This paper puts forward a learning mechanism to obtain the users′ preferences by using their evaluation of the services.On this basis,it proposes a dynamic adaptive service selection algorithm based on the reputation and the multi-attribute decision making theory.The algorithm,firstly,can generate the factor of the user′s preference by means of the obtained preference information.Then it selects the most suitable service to recommend to the user with the help of the services′ reputation and the weighted Euclidean distance between the candidate services and the user′s preferences.At last,a prototype system is built to verify the effectiveness and the availability of the proposed algorithm.