Advertisement
Published in:
2005 | OriginalPaper | Chapter
User-Class Based Service Acceptance Policy Using Cluster Analysis
Authors : Hea-Sook Park, Yan Ha, Soon-Mi Lee, Young-Whan Park, Doo-Kwon Baik
Published in: Distributed Computing and Internet Technology
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
This paper suggests a new policy for consolidating a company’s profits by segregating the clients using the contents service and allocating the media server’s resources distinctively by clusters using the cluster analysis method of CRM, which is mainly applied to marketing. For the realization of a new service policy, this paper analyzes the level of contribution vis-à-vis the clients’ service and profits through the cluster analysis of clients’ data applying the K-Means Method. Clients were grouped into 4 clusters according to the contribution level in terms of profits. In addition, to evaluate the efficiency of CRFS within the Client/Server environment, the acceptance rate per class was determined. The results of the experiment showed that the application of CRFS led to the growth of the acceptance rate of clients belonging to the cluster as well as the significant increase in the profits of the company.