Application Of Data Mining Technology To The Life-Insurance Market Analysis

Data Mining (DM) is from the large, incomplete, noise and ambiguous, random data, including the implicit in the extraction, people do not know in advance but it is potentially useful information and knowledge Process. since the reform and opening up of 30 years, China has made in the economic field attention from the Who's achievements at the same time, the worldwide information revolution is rising, using computer technology data processing capacity of a substantial increase for data and information-intensive insurance Industry, how to use Massive's business data resources, identify the internal laws of the market, better decision-making and business planning, enhance core competitiveness of enterprises, data mining technology is a very good tool.Life in the insurance market in a large proportion of the fierce market competition which allows the company must continue to tap their own potential, improve service quality; data mining techniques applied to the life insurance market analysis, determined to find an effective, innovative, The potential value of market information, or laws, good for business operators and decision-making departments to provide support for making important policy decisions is of great significance.Based on the data mining of theoretical research, described how the life insurance industry in accordance with the actual situation and needs of data mining techniques applied to the life insurance market in the analysis. First of all, the whole of data mining techniques were introduced and grasp, introduced the Data Mining at home and abroad on the status quo, and the definition of the main features, analysis, workflow and Technology and other issues, discussing the data mining algorithm in the life insurance industry Market analysis in the field of application forms and implementation steps. Of the data mining system , it is to achieve the general process and structure. Design and Implementation of a C/S framework, based on Windows + SQL Server platform for the life insurance data mining system LDMS. And then focus on the core module system, focusing on the life insurance industry with specific knowledge of how to construct a life insurance subsidiary life insurance data warehouse; details on the definition of association rules, the mining association rules and the use of the steps Fp-growth algorithm association rules Mining, the decision tree and the advantages and disadvantages of several typical algorithm is a summary, the combination of mining needs to achieve a scalable decision tree classification algorithm design, and cross-selling of mining association rules and customer segmentation results of the classification of Mining Understand the results and its business was an example, so that the life insurance companies in the marketing process, in a targeted manner to explore, develop products, cost-saving help.Finally, the research work carried out summary, the paper pointed out the inadequacy of the existing and proposed next step in the direction.