Description
A comprehensive introduction to flexible, efficient tools for describing massive data sets to improve the scalability of data analysis.
About the Author
Graham Cormode is a Professor in Computer Science at the University of Warwick, doing research in data management, privacy and big data analysis. Previously, he was a principal member of technical staff at AT&T Labs-Research. His work has attracted more than 14,000 citations and has appeared in more than 100 conference papers, 40 journal papers, and been awarded 30 US Patents. Cormode is the co-recipient of the 2017 Adams Prize for Mathematics for his work on Statistical Analysis of Big Data. He has edited two books on applications of algorithms and co-authored a third. Ke Yi is a Professor in the Department of Computer Science and Engineering, Hong Kong University of Science and Technology. He obtained his PhD from Duke University. His research spans theoretical computer science and database systems. He has received the SIGMOD Best Paper Award (2016), a SIGMOD Best Demonstration Award (2015), and a Google Faculty Research Award (2010). He currently serves as an Associate Editor of ACM Transactions on Database Systems and IEEE Transactions on Knowledge and Data Engineering.
Reviews
'A very thorough compendium of sketching and streaming algorithms, and an excellent resource for anyone interested in learning about them, understanding how they work and deploying them in applications. Good job!' Piotr Indyk, Massachusetts Institute of Technology
Book Information
ISBN 9781108477444
Author Graham Cormode
Format Hardback
Page Count 278
Imprint Cambridge University Press
Publisher Cambridge University Press
Weight(grams) 510g
Dimensions(mm) 234mm * 157mm * 19mm