Analysis And Design Of Insurance Industry Information System Based On Data Mining

With the popularity of the concept of data mining, People began to re-examine theimportance of the customers in the enterprise development.At the same time, facing the trendof economic globalization, information as the core content of the overall marketing is alreadyknown as the core of enterprise information technology and management techniques that isone of the key factors for marketing success.Consequently An excellent model of informationmanagement system is particularly important.。In this thesis,in-depth analysis data mining technology to clear Insurance informationmanagement needs.At the same tine,face the Classification technical defects of Insurance andInformation management mode, traditional management methods loose, with weightedentropy decision tree classification, proposed based on weighted entropy decision treeInsurance solutions for information management system. The program is the use of weightedentropy Dedcisions, Allocated for the categories of information entropy value so as to achievethe purpose of the overall management program.According to basic information of insurancecompanies analysis, the C4.5decision tree data mining algorithm is applied to the insuranceinformation management system, Automatically generated decision classification tree that isvaluable and easy to understand.Only in this way can find the management informationfeature, targeted to improve the management system and the management tools of theinsurance industry, finally improve management efficiency.In addition, To optimize thebusiness and customer communication, with the point of functional modules of insuranceinformation management system, provides an important safeguard customer informationsources by the mainstream of the JSP and SQL Server2005Technology.Finally, this thesis using the analysis result shows that Insurance informantionmanagement system which uses new weighted entropy performs a strong versatility and betterscalability.