Greedy Algorithms for Granular Computing Problems in Spatial Granulation Technique

In this paper we describe the use of kind of greedy algorithms for the efficient digital data processing by means of conversion to the space granular representation. The wide domains of computer technique using for the data extraction, processing and collection depends on the efficient algorithms and apparatus for the data manipulation. The examples of the “umbrella” terms in Artificial Intellect problems is Data Mining (DM) and Information Granulation (IG). Both DM and IG includes the different type approaches to the data processing and understanding. The common parts of two techniques is the data clustering (data granulation in the wide sense). It provides the high efficiency of designed algorithms by using natural data incompleteness, inaccuracy, incorrectness and other properties of Soft Computing. As a result, for the data granulation problems we provide the efficient algorithms (greedy algorithms), based on the granulation theory.