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Binding: PaperbackDewey Decimal Number: 004 EAN: 9781402030048 Edition: 2nd ISBN: 1402030045 Label: Springer Manufacturer: Springer Number Of Items: 1 Number Of Pages: 332 Publication Date: December 20, 2004 Publisher: Springer Studio: Springer Accessories:
Browse for similar items by category: Click to Display Editorial Review: Product Description: Interested in how an efficient search engine works? Want to know what algorithms are used to rank resulting documents in response to user requests? The authors answer these and other key information retrieval design and implementation questions. This book is not yet another high level text. Instead, algorithms are thoroughly described, making this book ideally suited for both computer science students and practitioners who work on search-related applications. As stated in the foreword, this book provides a current, broad, and detailed overview of the field and is the only one that does so. Examples are used throughout to illustrate the algorithms. The authors explain how a query is ranked against a document collection using either a single or a combination of retrieval strategies, and how an assortment of utilities are integrated into the query processing scheme to improve these rankings. Methods for building and compressing text indexes, querying and retrieving documents in multiple languages, and using parallel or distributed processing to expedite the search are likewise described. This edition is a major expansion of the one published in 1998. Besides updating the entire book with current techniques, it includes new sections on language models, cross-language information retrieval, peer-to-peer processing, XML search, mediators, and duplicate document detection. Average Rating:
 Rating:  - Easily the best intro to the IR field - Simple, very readable, practical and directly applicable Easily the best introduction to the field of IR. Its hallmarks are: 1. very readable (concepts presented in layman terms) and directly applicable (you can literally read and apply the concepts in the real world) 2. excellent survey of the field with an comprehensive compedium of references for further reading (surveys, topical and detailed references) 3. the only book with latest information on IR strategies and utilities - so far (May 2008) For the learnings you will ... Read More Rating:  - Poor content and presentationThis book presents information retrieval in an incomprehensible fashion. The content appears to have been cut and pasted from diverse unrelated sources with no effort put into massaging the parts into a coherent whole. There are several mistakes, typos, and wrong formulas throughout the book. Often concepts and abbreviation pop out without any context. Loose statements that are vague and hard to understand are made in several places. The book also fails to use a consistent style in its presentation. ... Read More Rating: - A good alternative to "Modern Information Retrieval"This is a very clear and current book on information storage and retrieval. If you are assigned this book as a textbook in a class, then the book is going to make the task of understanding the material much easier. All of the algorithms are clearly explained and the background material in probability is clearly outlined with good examples and figures. However, I still think I prefer Modern Information Retrieval for the theory of information storage and retrieval. It's out of print, but you can easily ... Read More Rating: - Excellent coverage of IR topicsThis book provides an excellent blend of theoretical and practical knowledge of the IR field, particularly for those of us with a computer science background, yet no practical working experience in IR. In my opinion, the math is an essential part of expressing the concepts more formally, so it was refreshing to see the authors incorporate just enough formulae, but no more. This book is not going to provide you with a set of recipes for building an indexing or search engine, nor would I expect it do so. ... Read More Rating:  - Mistakes in Bayes explanationsContains a bad mathematical mistake in section 2.2.1 on page 22. The probability P(win|sunny,good-shortstop) cannot be derived from P(win|sunny) and P(win|good-shortstop). It can take any value, even zero. Suppose, shortstop is a vampire and plays good only on cloudy weather, and on sunny weather he always leads his team to defeat. It doesn't contradict to having positive P(win|sunny) and P(win|good-shortstop). 
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