Managing Gigabytes: Compressing and Indexing Documents and Images, Second Edition

Managing Gigabytes is the best book out there on information retrieval. If you're interested in implementing your own IR system, there's nothing available that comes close to this book. But the book is good not just because it's the only one out there: the writing is excellent, the algorithms are presented clearly and explained well, and the coverage is thorough. Additionally, the coverage of compression algorithms is the best I've found in any book. All algorithms and pseudo-code in the book are presented clearly enough such that any competent programmer should be able to implement them. If all else fails, however, the free downloadable source code for the mg system can fill in any gaps.All in all, this is the best computer science book I've purchased in years. I wish all CS books were written like this one: it doesn't skimp on the theory or on the implementation details.

This is the only book there is that will actually teach you how to build an information retrieval system (aka search engine). It discusses all the algorithms and tradeoffs, and comes with free downloadable source code to experiment with. Some of the material is standard, but covered in more implementation detail here than anywhere else. Some of the material is novel: you won't find better coverage of compression unless you hand-assemble twenty research papers, and reverse-engineer them to figure out how they're implemented. But with "Managing Gigabytes", it's all here. (Although, after a particularly envigorating discussion of how to string together a bunch of techniques to compress their corpus and save a couple 100MB, I did a check and found you could buy 512MB of RAM for less than the cost of the book. Knowledge is Power, but sometimes a little cash is more powerful.) The only negative is that this book is not called "Managing Terabytes", as the first edition promised/threatened it might be. RAM and disk are cheap, but not that cheap, and for now terabytes (and sometimes petabytes) are managed only by NASA, Google, and a few others. I can't wait to see the third edition!

This is one of those rare books that succeeds both on a theoretical and practical level. The theory underlying management and retrieval of large collections of mixed text and image data is thoroughly covered. The authors' experience in developing the accompanying software shines through in the clarity of their explanations and enables them to give practical information regarding the techniques discussed. The software is not just of academic interest, either - an appendix describes a digital library, accessible over the web, that is supported by the mg software. In summary, this is a great book - readable, thorough and practical.

Managing Gigabytes is a must read for anyone iterested in how to transmit, access, store, and search large amounts of data. I'm the President and CTO of Aladdin Systems, Inc, the creators of the StuffIt compression product line for Mac and Windows, and I find it an invaluable addition to my reference library. The authors take complex information and present it in an organized, easy to read format, suitable for novices to experts. I highly recommend this book.

This text sets the standard for future information retrieval texts and has replaced the Salton books as the canonical academic text.The second edition is highly readable and contains a thorough updating of the algorithms and data structures in the field.I like the text because of its readability, conciseness, thoroughness, and attention to detail. The comparisons of algorithms on realistic sized collections is unparalleled in other texts.I have used this text for the past 5 years in a graduate level information storage and retrieval class but I believe it has a much wider audience due to the quality of writing.Additionally, the free availability of the mg system which implements many of the best algorithms of the text allows the reader/student to take advantage of the technology without having to start from scratch.Highly recommended.