Peter Kieseberg, Lukas Daniel Klausner, Andreas Holzinger
{"title":"现实世界分析过程中的失真","authors":"Peter Kieseberg, Lukas Daniel Klausner, Andreas Holzinger","doi":"10.31219/osf.io/psz9y","DOIUrl":null,"url":null,"abstract":"In discussions on the General Data Protection Regulation (GDPR), anonymisation and deletion are frequently mentioned as suitable technical and organisational methods (TOMs) for privacy protection. The major problem of distortion in machine learning environments, as well as related issues with respect to privacy, are rarely mentioned. The Big Data Analytics project addresses these issues.","PeriodicalId":44543,"journal":{"name":"ERCIM News","volume":null,"pages":null},"PeriodicalIF":0.1000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Distortion in Real-World Analytic Processes\",\"authors\":\"Peter Kieseberg, Lukas Daniel Klausner, Andreas Holzinger\",\"doi\":\"10.31219/osf.io/psz9y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In discussions on the General Data Protection Regulation (GDPR), anonymisation and deletion are frequently mentioned as suitable technical and organisational methods (TOMs) for privacy protection. The major problem of distortion in machine learning environments, as well as related issues with respect to privacy, are rarely mentioned. The Big Data Analytics project addresses these issues.\",\"PeriodicalId\":44543,\"journal\":{\"name\":\"ERCIM News\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.1000,\"publicationDate\":\"2019-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ERCIM News\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.31219/osf.io/psz9y\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERCIM News","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31219/osf.io/psz9y","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
In discussions on the General Data Protection Regulation (GDPR), anonymisation and deletion are frequently mentioned as suitable technical and organisational methods (TOMs) for privacy protection. The major problem of distortion in machine learning environments, as well as related issues with respect to privacy, are rarely mentioned. The Big Data Analytics project addresses these issues.
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