Small Summaries for Big Data

List of contents

1. Introduction; 2. Summaries for sets; 3. Summaries for multisets; 4. Summaries for ordered data; 5. Geometric summaries; 6. Graph summaries; 7. Vector, matrix and linear algebraic summaries; 8. Summaries over distributed data; 9. Other uses of summaries; 10. Lower bounds for summaries.

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.

Summary

The massive volume of data generated in modern applications requires the ability to build compact summaries of datasets. This introduction aimed at students and practitioners covers algorithms to describe massive data sets from simple sums to advanced probabilistic structures, with applications in big data, data science, and machine learning.

Additional text

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

Product details

• Authors: Graham Cormode, Graham (University of Warwick) Yi Cormode, Graham Yi Cormode, Cormode Graham, Cormode Ke Yi Graham Cormode, Ke Yi
• Publisher: Cambridge University Press ELT
• Languages: English
• Product format: Hardback
• Released: 31.10.2020
• EAN: 9781108477444
• ISBN: 978-1-108-47744-4
• No. of pages: 278
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; COMPUTERS / Computer Science, TECHNOLOGY & ENGINEERING / Signals & Signal Processing, COMPUTERS / Programming / Algorithms, COMPUTERS / Machine Theory, algorithms and data structures, Signal Processing, Algorithms & data structures, Mathematical theory of computation, Databases, Data analysis: general, Data science and analysis: general, Digital signal processing (DSP), COMPUTERS / Database Administration & Management