Multi-agent system for customer relationship management with SVMs tool

In this paper, we introduce multiple agents, knowledge discovery and data mining into customer relationship management (CRM) to set up the architecture of a multi-agent-based CRM system (MAB-CRM), and then use the SVMs-based approach to build up the decision support model which can classify the patterns obtained by the multiple agents into several decision levels, so that managers can pursue different decision-making activities according to the decision level of a pattern. Substantial experiments in the two-dimensional space show how the SVMs-based approach works. The practical problem from one Chinese company has been resolved by the SVMs-based approach. The results illustrate that this approach has an effective ability to learn the decision rules from the assessors' experience.

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