Arithmetic Based On Extension Theory In Data Ming Of CRM

Along with the development of computer network communication and Internet , the operation of the enterprise is becoming more automatic and then vast datum of the clients come into being . But in face of the vast datum the manager is facing the mess of indigent knowledge .In CRM it is imperious to find a new method to study and search after the rule in distribution of the commodity and offer valuable knowledge to the manager's decision-making , and the enterprise will win more profit. Data Ming is a useful method .Data Ming is the process of discovering interesting knowledge from large amounts of Data stored either in Databases , Data Warehouses , or other information repositories . It is mostly based on artificial intelligence machine study and statistics . Data Mining is used to analyze the information of the clients automatically and make out a inductive consequence . Then we can find the latent mode to forecast the actions of the clients and help the manager make a correct decision . Rough Set is a new useful method to Data Ming .Attribute Reduction is a important concept used in data analysis of Rough Set . Finding a fast and useful Attribute Reduction arithmetic is one of the hot topics . It is said that the calculation of the smallest reduction and all reductions is a NP problem . In this paper we analyze a few kinds of Attribute Reduction arithmetic in detail and give a new arithmetic based on matter element . Then these kinds of arithmetic are compared from the carrying out time and maturity and briefness . By an example we have proved that the arithmetic based on matter element is effective and predominant. In an example , the arithmetic is used to analyze the value of the clients in CRM to find reasonable and directive rules , and we combine the method with Extension Set , matter element commutation and. matter element's extension character to find new latent clients , offer a method of classing the clients and finding the latent clients .