Clustering Analysis of Library System Using Divisive Method

Abstract

Data mining is the automated or convenient extraction of patterns representing knowledge implicitly stored in large databases, data warehouses and other massive information repositories. Clustering has its roots in many areas, including data mining, statistics, biology, and machine learning. Nowadays, library has been constrained by its large amount of books. To overcome this problem, this paper presents a system which is used for the analysis of library system by using hierarchical clustering, divisive methods. In divisive methods of hierarchical cluster analysis, the clusters obtained at the previous step are subdivided into smaller clusters. So, the system provides the large books into several groups with their relevant field. This system provides the finding relevant and desired books with quickly.