A KDD System Based On Rough-Set And Its Application In Customer Relationship Management

Knowledge discovery in database(KDD), a new tool and technique for automatic and intelligent database analysis, is a quite active domain for the moment. Presently, Electronic Business is changing traditional business mode all over the world. How can we prevail in the competition of EB? CRM that can supply customer's resources and involved data analysis is the key. But a huge amount of data prevent us from discovering valuable customer mode, so the research of KDD applied in CRM is very significative.Now, there are many KDD systems applied in CRM. But the RS-Based KDD systems are few and they have many advantages. So, this paper is about the research of a RS-Based KDD system applied in CRM. Firstly, we obtain data from the CRM system, and convert them intorelevant decisiontable. Secondly, we complete and discretize the data in the decisiontable. Thirdly, we reduce the attribute and value. Lastly, we can conclude rules for making decision and establish logic ratiocination system.There may be much uncertain-decision information in CRM, and traditional RS can't be applied to model uncertain-decision information. So in order to solve this problem, we not only use VPRS(variable precision rough set)and ameliorate the arithmetic-reduced used in traditional RS, but also describe this uncertain-decision information by weight support and confidence of weight association rule.Finally, we carry out the RS-Based KDD system and obtain comparatively good result by experiment, which prove this paper is available.