Analysis of data clustering support for service

Abstract

With the current direction of service and cloud, unique characteristics of online software services impose new algorithmic requirements and cause differential applicability/ suitability of different clustering approaches in service analytics. In this paper, we investigate the efficiency and effectiveness of current important data clustering techniques, partitioning and hierarchical, for service analytics. It is our goal that results from this paper will serve as requirement guidelines for developing and deploying future intelligence services.