Ontology Self-Learning and Service Recommendation in Smart Environment

Abstract

In order to be able to provide users with personalized service, the paper analyses the characteristics and attributes of the user, and set up the user personalized ontology model via context in smart environment. Meanwhile, a Bayesian probability algorithm is designed that can automatically adjust according to user's preferences change. Combining with user activity, the user ontology model provides the user with a real-time active service model in the purpose of meeting user's demands, and presents the implementation pseudo code, which shows the usability of user model and algorithm.