摘要：Association rule granulation is a common data mining technique used to extract knowledge from the universe. To characterize the elements of the universe and to extract knowledge about the universe we classify the elements of the universe based on indiscernibility relation. However, in many information systems we find numerical attribute values that are almost similar instead of full identical. To handle such type of information system, we use (alfa, beta)-indiscernibility due to rough set on intuitionistic fuzzy approximation space with ordering rules. So, the classification results in a set of classes called granules and are basic building blocks of the knowledge about the universe. Granular computing processes these granules and produces possible patterns and associations. In this paper we study the concept of almost indiscernibility and knowledge granulation along with the association rules using granular computing method. We process the granules obtained as the result of classification and find the association rules between them
