{"title":"基于k均值和C&R树算法的医疗保险客户细分研究","authors":"Jianxin Bi","doi":"10.1109/SKG.2010.59","DOIUrl":null,"url":null,"abstract":"This paper applies such data mining techniques as clustering and classifying to customer segmentation based on insurance Customer Risk Contribution matrix. A solution for segmentation management based on Clementine is put forwarded. It is brought forward that the insurance customer segmentation method, which can provide decision bases for insurance companies’ making premium rate and controlling claim risk. At the same time, it makes segmentation management more scientific and lifts the capability of insurance market competition.","PeriodicalId":105513,"journal":{"name":"2010 Sixth International Conference on Semantics, Knowledge and Grids","volume":"281 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Research for Customer Segmentation of Medical Insurance Based on K-means and C&R Tree Algorithms\",\"authors\":\"Jianxin Bi\",\"doi\":\"10.1109/SKG.2010.59\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper applies such data mining techniques as clustering and classifying to customer segmentation based on insurance Customer Risk Contribution matrix. A solution for segmentation management based on Clementine is put forwarded. It is brought forward that the insurance customer segmentation method, which can provide decision bases for insurance companies’ making premium rate and controlling claim risk. At the same time, it makes segmentation management more scientific and lifts the capability of insurance market competition.\",\"PeriodicalId\":105513,\"journal\":{\"name\":\"2010 Sixth International Conference on Semantics, Knowledge and Grids\",\"volume\":\"281 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Sixth International Conference on Semantics, Knowledge and Grids\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SKG.2010.59\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Sixth International Conference on Semantics, Knowledge and Grids","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SKG.2010.59","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research for Customer Segmentation of Medical Insurance Based on K-means and C&R Tree Algorithms
This paper applies such data mining techniques as clustering and classifying to customer segmentation based on insurance Customer Risk Contribution matrix. A solution for segmentation management based on Clementine is put forwarded. It is brought forward that the insurance customer segmentation method, which can provide decision bases for insurance companies’ making premium rate and controlling claim risk. At the same time, it makes segmentation management more scientific and lifts the capability of insurance market competition.