Nima Hamta - M.Sc. student of industrial engineering, Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran
Jamal Shahrabi - PhD of industrial engineering, Assistant professor of industrial engineering department, Amirkabir University of Technology

Nowadays in a customer-oriented business environment, companies and organizations need to have a deep understanding of their customer requirements to use them in making important decision. This aim doesn’t meet unless data mining and knowledge extraction are applied and then attained knowledge is managed to make the best decisions. Therefore, in this paper we represent that how data mining can use as an efficient technique in order to extract knowledge in an integrated customer knowledge management framework. In this framework we illustrate that with available large data base, how can manage data to extract and analyze required information for making decision. At first an ideal decision-making process is defined. Then, by using achieved action or choice, a systematic approach is employed to extract knowledge. This process can improve data mining and knowledge management process and provide better information from customer’s behaviors that assist organizations to make appropriate decision.

Data mining approach; Knowledge management; Knowledge extraction; Decision-making process