| 基于改进Apriori 算法的保险产品推荐 |
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| 引用本文：朱天宇,谭文安.基于改进Apriori 算法的保险产品推荐[J].上海第二工业大学(中文版),2022,39(2):172-176 |
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| 基金项目:国家自然科学基金项目(61672022, U1904186), 上海第二工业大学电子信息类专业硕士协同创新平台建设项目资助 |
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| 中文摘要:为了加强保险业务员业务能力, 提高被推荐保险产品的成交率, 基于经典关联规则挖掘算法Apriori, 提出了
一种改进算法Apriori based on difference set(DS_Apriori) 来计算符合条件的保险产品。贡献包括: ① 通过以键值方
式重新组织数据、根据时序划分数据集、降低迭代搜索的次数等方式来提高算法执行效率; ② 通过以客户为主键
聚合事务数据来挖掘潜在关联规则, 实现精准推送。实验表明所提出的DS_Apriori 算法执行效率优于Apriori 等算
法, 可以给保险业务员提供业务指导, 精准推荐最符合推荐条件的保险产品。 |
| 中文关键词:关联规则 差集 Apriori 算法 保险推荐 |
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| Insurance Product Recommendation Based on Improved Apriori |
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| Abstract:In order to enhance the business capability of insurance salesmen and improve the turnover rate of recommended insurance
products, an improved algorithm Apriori based on difference set (DS_Apriori) is proposed to calculate the eligible insurance products
based on the classical association rule mining algorithm Apriori. The contributions include ① improving the algorithm execution
efficiency by reorganizing the data in key-value way, dividing the data set according to the time sequence, and reducing the number of algorithm iterations; ② mining the potential association rules by aggregating the transaction data with the customer as the main key to achieve accurate pushing. The experiments show that the proposed DS_Apriori algorithm performs better than algorithms such as
Apriori. It can provide business guidance to insurance salesmen and accurately recommend the insurance products that best meet the
recommended conditions. |
| keywords:association rule difference set Apriori algorithm insurance recommendation |
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