期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2016
卷号：7
期号：3
页码：32-35
语种：English
出版社：Ayushmaan Technologies
摘要：CURE Clustering divides the data sample into groups by identifying few representative points from each group of the data sample. This paper presents enhanced CURE as a clustering technique for data mining, in this approach we have a specially designed pattern as representative to form enhancement in CURE clustering to make it more usable efficiently on big data. Oracle 11G is used as backend with its silent feature of storing big data. The supervised trained model used to analyze this pattern to enhancing the CURE clustering which execute their function by specified parameter or value. This algorithm makes clustering easier and applicable on huge data by reducing time complexity.
