Orthogonal array construction and confidentiality in both survey and data-mining contexts

调查和数据挖掘环境中的正交阵列构造和机密性

• 批准号: 341784-2007
• 负责人: Lu, Wilson
• 金额: $ 1.02万
• 依托单位: Acadia University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2007
• 资助国家: 加拿大
• 起止时间: 2007-01-01 至 2008-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=363424
• 关键词: Orthogonal; array; construction; confidentiality; both

My research interests for the next few years will be primarily focused on developing adaptive statistical methods and investigating their theoretical properties for the analysis of large and complex datasets.In the context of complex surveys, protecting sensitive information from disclosure has become more and more challenging as the magnitude of such surveys increases. Specific methodologies may involve constructing nearly-orthogonal mixed-level arrays, which by itself is an interesting research problem in the area of modern experimental design, especially when designing input settings for complex computer simulators, as the realistic surrogate to the much more complex physical phenomena, is desired.It is also worth noticing that the issues of maintaining confidentiality in large data warehouses, closely related to the above-mentioned research problem, has drawn significant interests after data-mining techniques have been widely used by government agencies and businesses in processing public access data that also includes sensitive information. In particular, I intend to explore issues relating to algorithmic strategies in the area of privacy-preserving data-mining research and expect the results to be quite influential to industries involved in data-mining.

我未来几年的研究兴趣将主要集中在开发自适应统计方法并研究其用于分析大型复杂数据集的理论特性。在复杂调查的背景下，随着此类调查规模的增加，保护敏感信息不被泄露变得越来越具有挑战性。具体方法可能涉及构建近正交的混合级阵列，这本身就是现代实验设计领域中一个有趣的研究问题，特别是在为复杂的计算机模拟器设计输入设置时，作为更复杂的物理现象的现实替代品。还值得注意的是，与上述研究问题密切相关的大型数据仓库中的机密性维护问题已引起人们的关注。 政府机构和企业广泛使用数据挖掘技术来处理包括敏感信息在内的公共访问数据后，人们产生了兴趣。特别是，我打算探讨隐私保护数据挖掘研究领域中与算法策略相关的问题，并期望研究结果对涉及数据挖掘的行业产生相当大的影响。