ITR: Collaborative Research: A Data Mining and Exploration Middleware for Grid and Distributed Computing

ITR：协作研究：用于网格和分布式计算的数据挖掘和探索中间件

• 批准号: 0325013
• 负责人: Robert Grossman
• 金额: $ 31.57万
• 依托单位: University of Illinois at Chicago
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-11-01 至 2009-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0325013&HistoricalAwards=false
• 关键词: ITR; Collaborative; Research; Data; Mining

The purpose of this project is to develop and implement a middleware that allows mining and analysis of distributed data. The research will address an increasing interest in the exploration and mining of the large volume of data that is generated by the business, scientific, engineering, academic and defense communities. Novel techniques will be developed in the following areas:Data and Policy Management Services: These services will provide organizational level access restriction capabilities for the owners of the data while allowing users to access a more efficient transport of data.Data Mining and Exploration Services: This framework will include a library of data mining tools that will work effectively for example if: data is distributed on multiple sites, the user has varying privileges depending on what site they are accessing, a user wants to trade off computing time versus accuracy or a user wants to access the site remotely.Scheduling and Replication Services: System administration will be based upon policies at the participating organizations and their established privileges for users. Computation and data will be scheduled jointly to optimize metrics.This combination of distributed computing and data mining will be made widely available to students, researchers, and other interested groups in government, industry and education.

这个项目的目的是开发和实现一个允许挖掘和分析分布式数据的中间件。该研究将解决对商业、科学、工程、学术和国防社区产生的大量数据的探索和挖掘日益增长的兴趣。将在以下领域开发新技术：数据和策略管理服务：这些服务将为数据所有者提供组织级访问限制功能，同时允许用户访问更有效的数据传输。数据挖掘和探索服务：该框架将包括一个有效工作的数据挖掘工具库，例如：数据分布在多个站点上，用户根据他们访问的站点拥有不同的特权，用户希望在计算时间和准确性之间进行权衡，或者用户希望远程访问站点。调度和复制服务：系统管理将基于参与组织的策略及其为用户建立的特权。计算和数据将共同安排以优化指标。这种分布式计算和数据挖掘的结合将广泛地提供给学生、研究人员以及政府、工业和教育领域的其他感兴趣的团体。