Managing uncertainty in location based applications

In previous work we introduced the idea of user modeling as a means of reducing uncertainty in location tracking of human-controlled moving objects. We used the name roving users (RU for short) to refer to this subset of moving objects. In this paper we discuss the issue of reducing the complexity of the user model caused by variables with high number of possible values. We show how self organizing maps (SOM) could be used to classify values of a certain variable such that the classes are used - rather than actual values - in calculating the conditional probabilities of child variables. We support our proposed technique with some experimental results