| Data mining is a process of extracting valid, previously unknown, comprehensible, and actionable information from large databases. Along with the development of information technology at very fast speed , more and more data from various fields are increasing continually. At the same time ,data mining technology is being developed continually and transferred to application speediness. Along with the rapid expand and competing impetuosity of insurance market, it should be a trend that data mining was applied to insurance market data analysis for improving share of market and comprehending of customer purchasing behavior.In this paper, we go deep into the field of insurance industry and study data mining and data warehouse. We expound application of data mining and data warehouse in customer analysis of insurance industry. The majority of our work is summarized here:1. Through analysis of basic flow in insurance industry, we explained many aspects in insurance industry such as cross-sell,customer subdivision,customer response and the application of data mining and data warehouse technology in dealing with these problems. 2. Starting with concept of data warehouse, we designed and realized the concept model and logic model of data warehouse. 3. Starting with data mining technology , we realized some algorithms, include classify,clustering,and association rule and explained the application in insurance customer analysis. 4. For classify algorithm, we described SLIQ decision tree in detail, and bring forward an analysis model of insurance customer subdivision. 5. For clustering algorithm, we described forward an analysis model of customer response. 6. For association rule algorithm, we described FP-growth algorithm in detail and bring forward an analysis model of cross-sell. 7. We accomplished a data mining insurance customer analysis system-LIMiner. In this paper, we described the architecture, data models and every functional module of the system in detail. |
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