{"title":"CRM系统数据挖掘中的隐私保护算法","authors":"Shashidhar Virupaksha, G. Sahoo, A. Vasudevan","doi":"10.1109/ICCSP.2014.6950121","DOIUrl":null,"url":null,"abstract":"Organizations have a huge customer base and thus they use data mining tools to study their customers. However there is risk of sensitive information about individuals which can be gained also during this process. Hence data that is used for data mining has to be protected. There are some privacy protection algorithms which ensure privacy and protect data. These algorithms preserve privacy but data mining results significantly. In this paper we propose a clustering based noise addition that not only preserves privacy but also ensures effective data mining. Data characteristics are identified using clustering technique and noise is added within the clusters thus retaining the data characteristics.","PeriodicalId":149965,"journal":{"name":"2014 International Conference on Communication and Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Privacy preservation algorithm in data mining for CRM systems\",\"authors\":\"Shashidhar Virupaksha, G. Sahoo, A. Vasudevan\",\"doi\":\"10.1109/ICCSP.2014.6950121\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Organizations have a huge customer base and thus they use data mining tools to study their customers. However there is risk of sensitive information about individuals which can be gained also during this process. Hence data that is used for data mining has to be protected. There are some privacy protection algorithms which ensure privacy and protect data. These algorithms preserve privacy but data mining results significantly. In this paper we propose a clustering based noise addition that not only preserves privacy but also ensures effective data mining. Data characteristics are identified using clustering technique and noise is added within the clusters thus retaining the data characteristics.\",\"PeriodicalId\":149965,\"journal\":{\"name\":\"2014 International Conference on Communication and Signal Processing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Communication and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSP.2014.6950121\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Communication and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSP.2014.6950121","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Privacy preservation algorithm in data mining for CRM systems
Organizations have a huge customer base and thus they use data mining tools to study their customers. However there is risk of sensitive information about individuals which can be gained also during this process. Hence data that is used for data mining has to be protected. There are some privacy protection algorithms which ensure privacy and protect data. These algorithms preserve privacy but data mining results significantly. In this paper we propose a clustering based noise addition that not only preserves privacy but also ensures effective data mining. Data characteristics are identified using clustering technique and noise is added within the clusters thus retaining the data characteristics.