Mining Distributed, High-Speed, Time-Variant Data Streams

挖掘分布式、高速、时变数据流

• 批准号: DP0558879
• 负责人: Prof Xue Li
• 金额: $ 32.13万
• 依托单位: The University of Queensland
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2005
• 资助国家: 澳大利亚
• 起止时间: 2005-01-01 至 2008-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP0558879
• 关键词: Mining; Distributed; Speed; Time; Variant

With the high-speed and large volume of data generation, the data mining research community is facing an unprecedented challenge to provide instant data mining outcomes for prompt usage. Getting access to derived information from multiple, dynamically changing data is vital for many business, science and security services. Extended networks of sensors and other devices assist many environments with data collection that should be correlated and processed towards discovery of dependencies, regularities and patterns. Data mining tools, especially of this new generation, are capable of dealing with data streams, and they offer great benefits for users from many industry sectors; defence, health management, security, commerce and science.

随着数据产生的速度和数量的增加，数据挖掘研究界正面临着前所未有的挑战，即提供即时的数据挖掘结果以供及时使用。从多个动态变化的数据中获取派生信息对于许多商业、科学和安全服务至关重要。传感器和其他设备的扩展网络帮助许多环境进行数据收集，这些数据应该被关联和处理，以发现依赖关系、依赖关系和模式。数据挖掘工具，特别是新一代的数据挖掘工具，能够处理数据流，为国防、健康管理、安全、商业和科学等许多行业的用户提供了巨大的好处。