In this fully updated second edition of the highly acclaimed Managing Gigabytes , authors Witten, Moffat, and Bell continue to provide unparalleled coverage of state-of-the-art techniques for compressing and indexing data. Whatever your field, if you work with large quantities of information, this book is essential reading–an authoritative theoretical resource and a practical guide to meeting the toughest storage and access challenges. It covers the latest developments in compression and indexing and their application on the Web and in digital libraries. It also details dozens of powerful techniques supported by mg, the authors’ own system for compressing, storing, and retrieving text, images, and textual images. mg’s source code is freely available on the Web. * Up-to-date coverage of new text compression algorithms such as block sorting, approximate arithmetic coding, and fat Huffman coding * New sections on content-based index compression and distributed querying, with 2 new data structures for fast indexing * New coverage of image coding, including descriptions of de facto standards in use on the Web (GIF and PNG), information on CALIC, the new proposed JPEG Lossless standard, and JBIG2 * New information on the Internet and WWW, digital libraries, web search engines, and agent-based retrieval * Accompanied by a public domain system called MG which is a fully worked-out operational example of the advanced techniques developed and explained in the book * New appendix on an existing digital library system that uses the MG software Amazon.com Review Of all the tasks programmers are asked to perform, storing, compressing, and retrieving information are some of the most challenging–and critical to many applications. Managing Gigabytes: Compressing and Indexing Documents and Images is a treasure trove of theory, practical illustration, and general discussion in this fascinating technical subject. Ian Witten, Alistair Moffat, and Timothy Bell have updated their original work with this even more impressive second edition. This version adds recent techniques such as block-sorting, new indexing techniques, new lossless compression strategies, and many other elements to the mix. In short, this work is a comprehensive summary of text and image compression, indexing, and querying techniques. The history of relevant algorithm development is woven well with a practical discussion of challenges, pitfalls, and specific solutions. This title is a textbook-style exposition on the topic, with its information organized very clearly into topics such as compression, indexing, and so forth. In addition to diagrams and example text transformations, the authors use “pseudo-code” to present algorithms in a language-independent manner wherever possible. They also supplement the reading with mg–their own implementation of the techniques. The mg C language source code is freely available on the Web. Alone, this book is an impressive collection of information. Nevertheless, the authors list numerous titles for further reading in selected topics. Whether you’re in the midst of application development and need solutions fast or are merely curious about how top-notch information management is done, this hardcover is an excellent investment. –Stephen W. Plain Topics covered: Text compression models, including Huffman, LZW, and their variants; trends in information management; index creation and compression; image compression; performance issues; and overall system implementation.