Offers both students and professionals guidance on large-scale information systems. This resource describes a new generation of techniques for compressing, storing, and retrieving information--both machine readable text and optically scanned documents. Appropriate for information science and information retrieval courses.

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.

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