In order to supply services necessary for users intelligently in the ubiquitous computing, effective filtering of context information is necessary. But studies of context information filtering have not been made much yet. In order for filtering of context information, we can use collaborative filtering being used much at electric commerce, etc. In order to use such collaborative filtering method in the filtering of ubiquitous computing environment, we must solve such problems as first rater problem, sparsity problem, stored data problem and etc. In this study, in order to solve such problems, the researcher proposes the collaborative filtering method using types of context information. And as the result of applying this filtering method to MAUCA, the P2P mobile agent system, the researcher could confirm the average result of 7.7% in the aspect of service supporting function.