An introduction to information retrieval / Christopher D. Manning, P. Raghavan, Hinrich Schutze.
Tipo de material: TextoDetalles de publicación: Cambridge : Cambridge University Press, 2008 Descripción: XXI, 482 páginas ; 27 cmISBN: 9780521865715Tema(s): Catalogación bibliográfica -- Proceso de datos | Recuperación de la informaciónResumen: Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classificationand 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 bookâs supporting website to help course instructors prepare their lectures. INDICE: 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.Tipo de ítem | Biblioteca de origen | Signatura | Estado | Fecha de vencimiento | Código de barras | Reserva de ítems | Bibliografía recomendada |
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Manuales | 03. BIBLIOTECA INGENIERÍA PUERTO REAL | 025.436/MAN/int (Navegar estantería(Abre debajo)) | Disponible Ubicación en estantería | Bibliomaps® | 3745309709 |
RECUPERACIÓN DE LA INFORMACIÓN GRADO EN INGENIERÍA INFORMÁTICA Asignatura actualizada 2023-2024 |
Bibliografía. - índice.
Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classificationand 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 bookâs supporting website to help course instructors prepare their lectures.
INDICE: 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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