首页> 外文期刊>Information Sciences: An International Journal >On the connections between statistical disclosure control for microdata and some artificial intelligence tools
【24h】

On the connections between statistical disclosure control for microdata and some artificial intelligence tools

机译:关于微数据统计披露控制与一些人工智能工具之间的联系

获取原文
获取原文并翻译 | 示例
           

摘要

Statistical disclosure control (SDC) and artificial intelligence (AI) use similar tools for different purposes. This work describes the common elements of both areas to increase their synergy. SDC is a discipline that seeks to modify statistical data so that they can be published (typically by National Statistical Offices) without giving away the identity of any individual behind the data. When dealing with individual data (microdata in SDC jargon), both SDC procedures and AI knowledge integration procedures use similar principles for different purposes (masking data vs. improving its quality). Similarities can also be found for methods evaluating re-identification risk in SDC and data mining tools for making data consistent. This paper explores those methodological connections with the aim of stimulating interaction between both fields. In particular, data mining turns out to be a common interest of both fields. (C) 2003 Elsevier Science Inc. All rights reserved. [References: 60]
机译:统计披露控制(SDC)和人工智能(AI)使用类似的工具实现不同的目的。这项工作描述了这两个领域的共同要素,以增强它们的协同作用。 SDC是一门旨在修改统计数据的学科,以便可以在不泄露数据背后任何个人身份的情况下(通常由国家统计局发布)进行发布。在处理单个数据(SDC行话中的微数据)时,SDC过程和AI知识集成过程都出于不同目的使用相似的原理(掩盖数据与提高其质量)。在SDC中评估重新识别风险的方法和使数据一致的数据挖掘工具中也可以找到相似之处。本文探讨了这些方法上的联系,目的是促进两个领域之间的相互作用。特别地,事实证明数据挖掘是这两个领域的共同利益。 (C)2003 Elsevier Science Inc.保留所有权利。 [参考:60]

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号