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Search Engines: Information Retrieval in PracticeFebruary 2009
- Authors:
- Bruce Croft,
- Donald Metzler,
- Trevor Strohman
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Abstract
KEY BENEFIT: Written by a leader in the field of information retrieval, this text provides the background and tools needed to evaluate, compare and modify search engines. KEY TOPICS: Coverage of the underlying IR and mathematical models reinforce key concepts. Numerous programming exercises make extensive use of Galago, a Java-based open source search engine. MARKET: A valuable tool for search engine and information retrieval professionals.
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- References Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Appendixes Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Toward A Unified System for Text Management and Analysis Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Joint Analysis of Text and Structured Data Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Opinion Mining and Sentiment Analysis Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Topic Analysis Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Text Summarization Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Text Categorization Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Text Clustering Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Word Association Mining Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Overview of Text Data Analysis Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Recommender Systems Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Web Search Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Search Engine Evaluation Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Search Engine Implementation Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Feedback Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Retrieval Models Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Overview of Text Data Access Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- MeTA : A Unified Toolkit for Text Data Management and Analysis Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Text Data Understanding Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Background Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Introduction Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Preface Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
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Index Terms
- Search Engines: Information Retrieval in Practice
Reviews
George Pallis
Information retrieval is an increasingly important and rapidly growing area of computer science. This book gives a complete picture of how search engines are built, modified, and evaluated. The book contains 11 chapters. The first two are devoted to the basics of information retrieval and, in particular, the heart of search engines. They form an executive summary of what is to follow. Chapters 3 to 8 discuss the most important issues and techniques in search engines, such as crawling, text processing, indexing, ranking, and evaluation. Chapters 9 to 11 cover a variety of more advanced topics. Chapter 9 describes a number of algorithms for clustering and classification of documents; chapter 10 deals with social search?how the interactions or contributions of users determine the relevance of search results; and chapter 11 presents information retrieval approaches that are beyond bag-of-words?retrieval of Extensible Markup Language (XML), pictures, and music. In this book, Croft, Metzler, and Strohman provide a current, broad, and detailed overview for Web-scale search engines. I highly recommend it as the primary textbook for an undergraduate course. Numerous examples and figures are used throughout the book, to enhance its content. A set of exercises is also provided, at the end of each chapter, to further solidify the material covered. It is worth mentioning that the programming exercises are based on Galago?a fully functional, Java-based, open-source search engine that can be used to support real applications. The instructors can download lecture slides, solutions to select end-of-chapter problems, and test collections for exercises. This book could also serve as additional material for researchers and professionals. However, I would not recommend it for advanced graduate courses on information retrieval. Overall, this is an interesting and informative book that presents up-to-date coverage of search engines. I believe that it will appeal to a large audience. Online Computing Reviews Service
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