Study And Application Of Association Rules Algorithm On The Insurance Marketing

The Data Mining technology could effectively dispose of problem of managing and making good use of data and acquire correlative knowledge. As complexity and importance of insurance business , developing insurance data information has a significant scientific value and broad application prospect. Data Mining technology is an effective means of analyzing and processing data, which has already developed maturely gradually and applied to the part field and other departments. The thesis is mainly based on analysis,design,study and implementation of insurance marketing Data Mining system, mostly discusses the research of data mining technology of insurance marketing data warehouse.Based on the Assiciation Rules Data Mining technology, we choose classical algorithms-Apriori algorithm, by discovering a series of defect such as much candidate sets,access database inefficiently by two aspect from theory and the sample data applying, in order to come over the defect of Apriori, thesis put forward FP_growth algorithm, then explain that it is no way of Apriori to reach superiority of FP_growth in performance and efficiency. At the same time, thesis put forward algorithm implementation mechanism based on B/S structure according to FP_growth algorithm character. At last, it conclude completed job and analysis,outlook of future study.