A New Context-Aware Learning System for Predicting Services to Users in Ubiquitous Environment
Jieun Lee, Sanghoun Oh, Moongu Jeon · 2007
Abstract — This paper represents a new context-aware learning system to provide services in ubiquitous computing environment. The aim is to precisely decide which services each user provides. To achieve this goal, we design a preprocessing method (i.e., context modeling) to obtain good information which represents user’s characteristics from context-aware information (i.e., user profiles) which consists of states: who, when, where, why, what, and how: 5W1H. The proposed system applies the state-of-the-art naïve Bayesian Decision Theory, which is one of the statistical analyses based on probability theorem. Index Terms — context-aware application, naïve Bayesian classifier, and user’s preference learner