Architecture of Integrated Data Clustering Machine

作     者：ARIF Iqbal ARIF IQBAL;ZHOU YI-MING

作者机构：School of Computer Science & Engineering Beijing University of Aeronautics and Astronautics 

出 版 物：《Computer Aided Drafting,Design and Manufacturing》 (计算机辅助绘图设计与制造（英文版）)

年 卷 期：2009年第19卷第2期

页      面：43-48页

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0802[工学-机械工程] 

主　　题：data mining data clustering data clustering algorithms architecture framework 

摘      要：Data clustering is a significant information retrieval technique in today＇s data intensive society. Over the last few decades a vast variety of huge number of data clustering algorithms have been designed and implemented for all most all data types. The quality of results of cluster analysis mainly depends on the clustering algorithm used in the analysis. Architecture of a versatile, less user dependent, dynamic and scalable data clustering machine is presented. The machine selects for analysis, the best available data clustering algorithm on the basis of the credentials of the data and previously used domain knowledge. The domain knowledge is updated on completion of each session of data analysis.