Clustering Techniques and Hierarchical Distance Measure in Datamining - Angelin Rosy, M; Shyamala, D; Felix Xavier Muthu, M (International Journal of Computer Sciences and Engineering, 2025)
Data mining is extracting information from huge set of data. Clustering is a process of organizing object into unknown group. it deals with finding a structure in a collection of unlabeled data. Similar objects are grouped in one cluster and dissimilar are grouped in another cluster. The documents clustering will aims to group in unsupervised way. Clustering analysis is one of the main logical methods in data mining. Which focuses on the current popular and commonly used k-means algorithm? Clustering can be classified into partition method, hierarchical method, density based method, grid based method, and model based method. In hierarchical method are based on different distance measures. In each type calculate the distance between each data objects and all cluster centers .this paper provides a broad survey of the most basic techniques and identifies.