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http://dx.doi.org/10.3745/KIPSTD.2005.12D.3.461

User-Class based Service Acceptance Policy using Cluster Analysis  

Park Hea-Sook (경인여자대학 컴퓨터정보기술학부)
Baik Doo-Kwon (고려대학교 정보통신대학 컴퓨터학과)
Publication Information
The KIPS Transactions:PartD / v.12D, no.3, 2005 , pp. 461-470 More about this Journal
Abstract
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. In this case, CRM refers to the strategy of consolidating a company's profits by efficiently managing the clients, providing them with a more effective, personalized service, and managing the resources more effectively. For the realization of a new service policy, this paper analyzes the level of contribution $vis-\acute{a}-vis$ the clients' service pattern (total number of visits to the homepage, service type, service usage period, total payment, average service period, service charge per homepage visit) 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. Likewise, the CRFA (Client Request Filtering algorithm) was suggested per cluster to allocate media server resources. CRFA issues approval within the resource limit of the cluster where the client belongs. In addition, to evaluate the efficiency of CRFA within the Client/Server environment the acceptance rate per class was determined, and an evaluation experiment on network traffic was conducted before and after applying CRFA. The results of the experiments showed that the application of CRFA led to the decrease in network expenses and growth of the acceptance rate of clients belonging to the cluster as well as the significant increase in the profits of the company.
Keywords
Multimedia Contents; Admission Control; Cluster Analysis;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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