Tenant behavior analysis in software as a Service environment

Abstract

Software as a Service (SaaS) is an emerging model to deliver software over the Web as a service. With the fast growing of the SaaS business in the recent years, data mining application in SaaS environment becomes an attractive topic. While many existing Web mining technologies can be leveraged, SaaS has its own unique perspective. In this paper, we propose a model for SaaS tenant behavior analysis based on the unique perspective of SaaS environment. The corresponding algorithm to derive the metrics of the model by means of mining the tenant's collaboration indices from raw log is also presented. The derived collaboration indices can provide an important metric for efficiently launching data mining algorithm for customer analysis in a SaaS environment. Its effectiveness is verified through an experiment comparing the result for different types of tenants on a real SaaS service. © 2011 IEEE.