Comparative Analysis of K-Means and Kohonen-SOM data mining algorithms based on student behaviors in sharing information on facebook

Abstract

Clustering can be used for describing and analyzing of data. In this paper, the approach of Kohonen SOM and K-Means and HAC are discussed. After comparing these three methods effectively and reflect data characters and potential rules syllabify. This work will present new and improved results from large-scale datasets. With the development of information technology and computer science, high-capacity data appear in our lives. In order to help people analyzing and digging out useful information, the generation and application of data mining technology seem so significance. Clustering is the mostly used method of data mining.