Introduction to Information Retrieval

A class-tested and up-to-date textbook for introductory courses on information retrieval.

Class-tested and up-to-date textbook for introductory courses on information retrieval.

Autorentext
Christopher Manning is an Associate Professor of Computer Science and Linguistics at Stanford University. His research concentrates on probabilistic models of language and statistical natural language processing, information extraction, text understanding and text mining.

Klappentext
Class-tested and up-to-date textbook for introductory courses on information retrieval.


Zusammenfassung
Class-tested and coherent, this textbook teaches information retrieval, including web search, text classification, and text clustering from basic concepts. Ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students. Slides and additional exercises are available for lecturers.

Inhalt
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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