Class-tested and coherent, this groundbreaking new textbook teaches web-era information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. Written from a computer science perspective by three leading experts in the field, it gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Although originally designed as the primary text for a graduate or advanced undergraduate course in information retrieval, the book will also create a buzz for researchers and professionals alike.Read more
- Introduces all key concepts, requiring little prior knowledge
- All concepts are illustrated with figures and examples
- Supporting web site features lecture slides that follow the book, and a solutions manual for lecturers
Reviews & endorsements
“This is the first book that gives you a complete picture of the complications that arise in building a modern web-scale search engine. You'll learn about ranking SVMs, XML, DNS, and LSI. You'll discover the seedy underworld of spam, cloaking, and doorway pages. You'll see how MapReduce and other approaches to parallelism allow us to go beyond megabytes and to efficiently manage petabytes."
Peter Norvig, Director of Research, Google Inc.See more reviews
"Introduction to Information Retrieval is a comprehensive, up-to-date, and well-written introduction to an increasingly important and rapidly growing area of computer science. Finally, there is a high-quality textbook for an area that was desperately in need of one."
Raymond J. Mooney, Professor of Computer Sciences, University of Texas at Austin
“Through compelling exposition and choice of topics, the authors vividly convey both the fundamental ideas and the rapidly expanding reach of information retrieval as a field.”
Jon Kleinberg, Professor of Computer Science, Cornell University
H.Levkowitz, Choice Magazine
"Introduction to Information Retrieval is a comprehensive, authoritative, and well-written overview of the main topics in IR. The book offers a good balance of theory and practice, and is an excellent self-contained introductory text for those new to IR."
Olga Vechtomova, Computational Linguistics
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- Date Published: July 2008
- format: Hardback
- isbn: 9780521865715
- length: 496 pages
- dimensions: 260 x 185 x 31 mm
- weight: 1.03kg
- contains: 5 b/w illus. 47 tables 263 exercises
- availability: In stock
Table of Contents
1. Information retrieval using the Boolean model
2. The dictionary and postings lists
3. Tolerant retrieval
4. Index construction
5. Index compression
6. Scoring and term weighting
7. Vector space retrieval
8. Evaluation in information retrieval
9. Relevance feedback and query expansion
10. XML retrieval
11. Probabilistic information retrieval
12. Language models for information retrieval
13. Text classification and Naive Bayes
14. Vector space classification
15. Support vector machines and kernel functions
16. Flat clustering
17. Hierarchical clustering
18. Dimensionality reduction and latent semantic indexing
19. Web search basics
20. Web crawling and indexes
21. Link analysis.
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