SGER: Efficient Support for Mining Queries in Data Stream Management Systems

在许多应用领域，包括发布/订阅、流量监控、传感器网络和算法交易中，对海量数据流的连续查询的有效支持至关重要。因此，设计数据流管理系统（DSMS），以有效地支持这种查询，可靠地代表了当前研究的一个充满活力的领域。不幸的是，DSMS还不能有效地支持从数据流中提取新模式和知识所需的非常复杂的挖掘查询-尽管它们在重要的应用中是需要的，例如入侵检测和其他安全任务。设计用于支持挖掘任务的DSMS被称为归纳DSMS（因为它们从数据中引入新知识）。该项目的目标是通过（i）设计更快的数据流挖掘算法，以及（ii）扩展DSMS以支持有效地挖掘以DSMS查询语言表示的任务，以及（iii）构建归纳DSMS原型并在数据挖掘测试平台上对其进行评估，来开发归纳DSMS的支持技术。数据挖掘技术正在对不同的应用领域产生重大影响，包括商业，安全和科学。然而，挖掘代表信息时代命脉的海量数据流已被证明非常困难：这是解决这一挑战的第一个项目。一个广泛的科学，教育和经济活动将大大受益，一旦感应DSMS的愿景成为现实。 项目资金将支持博士生从事DSMS和数据挖掘研究。新技术将丰富几门研究生课程。通过出版物、报告和演示进行传播，可从http://wis.cs.ucla.edu/idsms获得。

Efficient support for continuous queries on massive data streams is critical in many application areas, including publish/subscribe, traffic monitoring, sensor networks, and algorithmic trading. Thus, designing data stream management systems (DSMS) to support such queries efficiently and reliably represents a vibrant area of current research. Unfortunately, DSMS cannot yet support efficiently the very complex mining queries required to extract new patterns and knowledge from data streams-- although they are needed in important applications, such as intrusion detection and other security tasks. DSMS designed to support mining tasks are called Inductive DSMS (since they induce new knowledge from data). This project's objective is to develop the enabling technology for Inductive DSMS by (i) designing faster data stream mining algorithms, and (ii) extending DSMS to support efficiently mining tasks expressed in the DSMS query language, and (iii) building an Inductive DSMS prototype and evaluating it on data mining testbeds. Data mining technology is having a major impact on diverse applications domains, including business, security, and science. However, mining the massive data streams that represent the lifeblood of the information age has proven very difficult: this is the first project addressing this challenge. A broad range of scientific, educational, and economic activities will benefit greatly once the vision of Inductive DSMS becomes reality. Project funds will support PhD students pursuing research on DSMS and data mining. The new technology will enrich several graduate courses. Dissemination is through publications, reports, and demos available from: http://wis.cs.ucla.edu/idsms.