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3946409
Foundations of Statistical Natural Language Processing
85% of respondents would recommend this to a friend
Nº de artículo:
3946409
UYU 3670
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What Stands Out
Comprehensive Coverage
Covers a wide range of statistical models and algorithms, making it a comprehensive resource for both students and professionals in the field of Natural Language Processing.
Practical Applications
Focuses on practical applications of statistical methods, enabling readers to effectively apply concepts to real-world NLP problems and projects.
Author Expertise
Authored by leading experts in the field, ensuring high-quality content that is both informative and authoritative, catering to both beginners and seasoned researchers.
Detalles de producto
| Publisher | The MIT Press |
| Publication date | June 18, 1999 |
| Edition | 1st |
| Language | English |
| Print length | 620 pages |
| ISBN-10 | 0262133601 |
| ISBN-13 | 978-0262133609 |
| Item Weight | 2.89 pounds (1.31 kg) |
| Reading age | 18 years and up |
| Dimensions | 8.27 x 1.18 x 9.29 inches (21 x 3 x 23.6 cm) |
| Grade level | 12 and up |
DESCRIPCIÓN DEL PRODUCTO
Foundations of Statistical Natural Language Processing
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Natural Language Processing Editorial Review
**Editorial Review of "Foundations of Statistical Natural Language Processing"** "Foundations of Statistical Natural Language Processing" emerges as a comprehensive and precise text that caters well to both novices and intermediates in the field of natural language processing (NLP). Compared to its counterparts, notably Jurafsky and Martin's classic work, this book chooses quality over quantity, presenting fewer problems in greater depth. This approach ensures that readers grasp concepts thoroughly and apply them effectively. The organization of the content is particularly commendable; readers appreciate the clarity and logical flow, which facilitates understanding and bridges the gap between theory and practical application. The book covers fundamental techniques in statistical NLP, such as language modeling and smoothing, in an accessible manner that does not overwhelm newcomers, yet still proves beneficial for readers with more experience. While the introductory chapters may take up Considerable space, they set a strong foundation for readers new to the subject. However, some critics highlight the omission of more advanced topics, suggesting that while it serves as an excellent introduction, those with a deeper background in NLP may need to seek supplementary resources for cutting-edge developments. Overall, the book receives strong recommendations for its clarity, comprehensive coverage, and its capacity to equip readers with both the theoretical understanding and practical skills required to tackle NLP challenges. It stands out as an essential text for anyone serious about diving into this evolving field. **
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ventajas
- In-depth exploration of topics with clear explanations and practical relevance.
- User-friendly organization that aids in comprehension, making it suitable for beginners.
- Comprehensive coverage of statistical approaches to language processing.
- Strong recommendations for both academic and practical applications, including programming.
Contras
- Some introductory chapters may be overly extensive for advanced readers.
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características y beneficios
- Comprehensive introduction to statistical natural language processing.
- Includes theory, algorithms, and mathematical and linguistic foundations.
- Detailed discussion of statistical methods for building NLP tools.
- Enables construction of custom implementations for students and researchers.
- Covers collocation finding, word sense disambiguation, probabilistic parsing, and information retrieval applications.
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