数据流：模型与算法

English | PDF | 2007 | 365 Pages | ISBN : 0387287590 | 23.05 MB

In recent years, the progress in hardware technology has made it possible for organizations to store and record large streams of transactional data. Such data sets which continuously and rapidly grow over time are referred to as data streams. Data Streams: Models and Algorithms primarily discusses issues related to the mining aspects of data streams rather than the database management aspect of streams. This volume covers mining aspects of data streams in a comprehensive style. Each contributed chapter, from a variety of well known researchers in the data mining field, contains a survey on the topic, the key ideas in the field from that particular topic, and future research directions.

Data Streams: Models and Algorithms is intended for a professional audience composed of researchers and practitioners in industry. This book is also appropriate for graduate-level students in computer science.

Charu C. Aggarwal obtained his B.Tech in Computer Science from IIT Kanpur in 1993 and Ph.D. from MIT in 1996. He has been a Research Staff Member at IBM since then, and has published over 90 papers in major conferences and journals in the database and data mining field. He has applied for, or been granted, over 50 US and International patents, and has twice been designated Master Inventor at IBM for the commercial value of his patents. He has been granted 14 invention achievement awards by IBM for his patents. His work on real time bio-terrorist threat detection in data streams won the IBM Epispire award for environmental excellence in 2003. He has served on the program committee of most major database conferences, and was program chair for the Data Mining and Knowledge Discovery Workshop, 2003, and a program vice-chair for the SIAM Conference on Data Mining, 2007. He is an associate editor of the IEEE Transactions on Data Engineering and an action editor of the Data Mining and Knowledge Discovery Journal. He is a senior member of the IEEE.

近年来，硬件技术的进步使得组织能够存储和记录大量交易数据的流。随着时间的不断增长而迅速增加的数据集被称为数据流。 《数据流：模型与算法》主要讨论了数据流方面的挖掘问题而不是数据流管理方面的问题。本卷以全面的方式涵盖了数据流的挖掘部分。每章都来自数据库和数据挖掘领域中许多知名研究者的贡献章节，包含对该主题的研究综述、该领域的关键思想以及未来的研究方向。

《数据流：模型与算法》旨在由工业界的学者和从业者组成的专业观众。这本书也适合计算机科学专业的研究生。 Charu C. Aggarwal于1993年在IIT Kanpur获得计算机科学学士学位，并于1996年从MIT获得博士学位。自那时以来，他一直是IBM的研究人员成员，并在数据库和数据挖掘领域的主要会议和期刊上发表了超过90篇论文。他申请了或被授予了50多项美国和国际专利，并因他的专利的商业价值而两次被评为IBM大师发明者。他曾获得14项由IBM颁发的发明成就奖，这些奖项都与他在数据流中的实时生物恐怖威胁检测工作有关。2003年。他曾在大多数主要的数据库会议上担任程序委员会成员，并在2003年的数据挖掘和知识发现研讨会中担任程序主席，在2007年的SIAM数据挖掘大会上担任联合副主席。他是IEEE Transactions on Data Engineering的副编辑，也是Data Mining and Knowledge Discovery期刊的顾问编辑。他是IEEE的高级会员。

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