Hinrich Schütze Christopher D. ManningCambridge University Press, 7/7/2008EAN 9780521865715, ISBN10: 0521865719Hardcover, 506 pages, 26 x 18.5 x 3.1 cmLanguage: EnglishClass-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. 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. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.1. Information retrieval using the Boolean model2. The dictionary and postings lists3. Tolerant retrieval4. Index construction5. Index compression6. Scoring and term weighting7. Vector space retrieval8. Evaluation in information retrieval9. Relevance feedback and query expansion10. XML retrieval11. Probabilistic information retrieval12. Language models for information retrieval13. Text classification and Naive Bayes14. Vector space classification15. Support vector machines and kernel functions16. Flat clustering17. Hierarchical clustering18. Dimensionality reduction and latent semantic indexing19. Web search basics20. Web crawling and indexes21. Link analysis.'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.
