Introduction to information retrieval
著者
書誌事項
Introduction to information retrieval
Cambridge University Press, 2008
大学図書館所蔵 件 / 全97件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
注記
Includes bibliographical references and index
内容説明・目次
内容説明
Class-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.
目次
- 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.
「Nielsen BookData」 より
