Data mining refers to extracting or “mining” knowledge from large amounts of data. It is also called a method of “knowledge presentation” where visualization and knowledge representation techniques are used to present the mined knowledge to the user. Thus, it plays an important role in extracting spatial patterns, features. It also performs presenting data regularity concisely and at higher conceptual levels to recognize spatial databases to accommodate data semantics as well as to achieve better performance, develops a visual feedback querying system to support data mining, it is an essential process where intelligent methods are applied in order to extract data patterns. In this article, a data mining algorithm is explored which is named CLAUMS and proved to be more efficient and effective than existing algorithm PAM. The proposed CLAUMS algorithm is more efficient comparing with respect to both time and memory complexity than PAM