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

随着数据的高速和大量生成，如何提供即时的数据挖掘结果以供及时使用，是数据挖掘研究界面临的前所未有的挑战。访问来自多个动态变化数据的派生信息对于许多业务、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收集数据，这些数据应该被关联和处理，以发现依赖关系、规律和模式。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，并为许多行业的用户提供了巨大的好处；国防、卫生管理、安全、商业和科学。

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.