Abstract
Information sources provide us with granules of information that must be transformed, analyzed and built into structures that support problem solving. One of the main goals of information granule calculi is to develop algorithmic methods for construction of complex information granules from elementary ones by means of available operations and inclusion (closeness) measures. These constructed complex granules represent a form of information fusion. Such granules should satisfy some constraints like quality criteria or/and degrees of granule inclusion in (closeness to) a given information granule. Information granule decomposition methods are important components of those methods. We discuss some information granule decomposition methods.