Data management bundle
Published on 20. November 2008
Book
Mixed media product
978-0-12-374864-5 (ISBN)
Description
Whatever your field, if you work with large quantities of information, this bundle is essential reading - an authoritative theoretical resource and a practical guide to meeting the toughest storage and access challenges.
Introduction to Data Compression is the best introduction and reference text on the art and science of data compression. Data compression techniques and technology are ever-evolving with new applications in image, speech, text, audio, and video; this third edition includes all the cutting edge updates you will need.
Managing Gigabytes provides unparalleled coverage of state-of-the-art techniques for compressing and indexing data. It covers the latest developments in compression and indexing and their application on the Web and in digital libraries
Bundled together to save you money, this is the best value, high quality resource on data management for students and professionals alike.
Introduction to Data Compression is the best introduction and reference text on the art and science of data compression. Data compression techniques and technology are ever-evolving with new applications in image, speech, text, audio, and video; this third edition includes all the cutting edge updates you will need.
Managing Gigabytes provides unparalleled coverage of state-of-the-art techniques for compressing and indexing data. It covers the latest developments in compression and indexing and their application on the Web and in digital libraries
Bundled together to save you money, this is the best value, high quality resource on data management for students and professionals alike.
More details
Language
English
Place of publication
San Francisco
United States
Publishing group
Elsevier Science & Technology
Target group
College/higher education
Weight
2570 gr
ISBN-13
978-0-12-374864-5 (9780123748645)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Ian H. Witten is a professor of computer science at the University of Waikato in New Zealand. He directs the New Zealand Digital Library research project. His research interests include information retrieval, machine learning, text compression, and programming by demonstration. He received an MA in Mathematics from Cambridge University, England; an MSc in Computer Science from the University of Calgary, Canada; and a PhD in Electrical Engineering from Essex University, England. He is a fellow of the ACM and of the Royal Society of New Zealand. He has published widely on digital libraries, machine learning, text compression, hypertext, speech synthesis and signal processing, and computer typography. Khalid Sayood received his BS and MS in Electrical Engineering from the University of Rochester in 1977 and 1979, respectively, and his Ph.D. in Electrical Engineering from Texas A&M University in 1982. In 1982, he joined the University of Nebraska, where he is the Heins Professor of Engineering. His research interests include data compression, joint source channel coding, and bioinformatics.