Data Mining by Clustering in Very Large Relational Databases

超大型关系数据库中的聚类数据挖掘

• 批准号: DP0663196
• 负责人: Prof Christopher Leckie
• 金额: $ 13.94万
• 依托单位: The University of Melbourne
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2006
• 资助国家: 澳大利亚
• 起止时间: 2006-01-01 至 2009-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP0663196
• 关键词: Data; Mining; Clustering; Very; Large

Many commercial and governmental entities possess very large relational data that cannot be feasibly analyzed by today's computers, e.g., gene expression data, product usage databases and telecommunication call records. The clustering tools developed in this project will have a significant benefit on many business processes that involve clustering this type of data, such as fraud detection and market segmentation.

许多商业和政府实体拥有非常大的关系数据，例如基因表达数据、产品使用数据库和电信通话记录，无法通过当今的计算机进行分析。该项目中开发的集群工具将对涉及此类数据集群的许多业务流程带来显着的好处，例如欺诈检测和市场细分。