Study Of Intelligent Customer Relationship Management System Based On Data Mining

Intelligent Customer Relationship Management System(ICRM),which is the combination of CRMS and artificial intelligence, is a promising research area. Data mining is an important tool to improve its abilities of management decision support. Data mining is the process of discovering connotative, previously unknown, potentially useful and understandable information from large datasets. Data from the database of decision domain is often uncertain and incomplete, and resulting in difficulty of knowledge discovery from this kind of data. This paper aimed to the characteristic of customer relationship management system, it is analyzed that the step and characteristic of the data mining course; For meet customer relationship management system which depend on business intelligence analyses even more than before , have put forward the solution based on the cluster's algorithm and rough set theory. After further investigating the defect of the fuzzy cluster's algorithm, provide its and improve algorithms correspondingly, and applied to the CRMS to find categorized rule, combining the Rough set theory on the basis of this foundation to mining the deeper decision rule. The concrete research contents are as follows: 1,This dissertation discuss the data mining dispose process which can support many data collections and many goals. The course model of data processing can be more suitable for the need of the practical work, can reduce the influence factor between the user and data mining people, promoting the application of data mining. 2,Through the analysis and research of the performance , shortcoming of the traditional cluster's algorithm, utilize cluster validity function solve the best cluster result problem , adopt automatic circulation strategy to produce cluster's valid numbers , this nodules has put forward a new improvement algorithm on the basis of FKM algorithm --FKMA algorithm, applied it to the customer classified rule mining. 3,On the foundation of the customer classified rule, probe into the Knowledge reduction by Rough set applied into uncertainty and incompleteness customer information system and the concrete approach which can educe the problem decisions or classified regulations. One set of computing methods has been designed for relevant numeric amount and collections quantity of rough set, thus received the more high-accuracy decision rule set. 4,On the base of above-mentioned work, researched the structure of IDSS based on the DMA, combining the modern customer relationship management idea, emphases on the system of intelligent CRM ,provide the plan of design function structure. The research work in the dissertation has partly solved the problems of discovering knowledge from the data which is certain or incomplete, made it possible for the data mining analysis technique to be further applied to customer relationship management decision.