04627nam a22005415i 4500 978-0-387-47534-9 DE-He213 20260521091919.0 cr nn 008mamaa 100301s2007 xxu| s |||| 0|eng d 9780387475349 99780387475349 10.1007/978-0-387-47534-9 doi CICY 006.312 23 Aggarwal, Charu C. editor. Data Streams [recurso electrónico] : Models and Algorithms / edited by Charu C. Aggarwal. Boston, MA : Springer US, 2007. XVIII, 354 p. online resource. text txt rdacontent computer c rdamedia recurso en línea cr rdacarrier text file PDF rda Advances in Database Systems, 1386-2944 ; 31 An Introduction to Data Streams -- On Clustering Massive Data Streams: A Summarization Paradigm -- A Survey of Classification Methods in Data Streams -- Frequent Pattern Mining in Data Streams -- A Survey of Change Diagnosis Algorithms in Evolving Data Streams -- Multi-Dimensional Analysis of Data Streams Using Stream Cubes -- Load Shedding in Data Stream Systems -- The Sliding-Window Computation Model and Results -- A Survey of Synopsis Construction in Data Streams -- A Survey of Join Processing in Data Streams -- Indexing and Querying Data Streams -- Dimensionality Reduction and Forecasting on Streams -- A Survey of Distributed Mining of Data Streams -- Algorithms for Distributed Data Stream Mining -- A Survey of Stream Processing Problems and Techniques in Sensor Networks. 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. COMPUTER SCIENCE. COMPUTER COMMUNICATION NETWORKS. DATABASE MANAGEMENT. DATA MINING. INFORMATION STORAGE AND RETRIEVAL SYSTEMS. INFORMATION SYSTEMS. MULTIMEDIA SYSTEMS. COMPUTER SCIENCE. DATA MINING AND KNOWLEDGE DISCOVERY. DATABASE MANAGEMENT. INFORMATION STORAGE AND RETRIEVAL. MULTIMEDIA INFORMATION SYSTEMS. COMPUTER COMMUNICATION NETWORKS. INFORMATION SYSTEMS APPLICATIONS (INCL.INTERNET). SpringerLink (Online service) Springer eBooks Printed edition: 9780387287591 Advances in Database Systems, 1386-2944 ; 31 http://dx.doi.org/10.1007/978-0-387-47534-9 Ver el texto completo en las instalaciones del CICY ddc ER 33676 33676 0 0 ddc 0 0 LE CICY CICY EL 2025-07-10 0 006.312 2025-07-10 08:40:01 2025-07-10 ER