Foundations of Statistical Natural Language Processing

by Christopher Manning and Hinrich Schütze
Foundations of Statistical Natural Language Processing cover
Good Books rating 4.2
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  • ID: 8368
  • Added: 2025-12-21
  • Updated: 2025-12-21
  • Reviews: 3
Reviews
Project MUSE · KB Cohen · 2002-01-01
essential 4.00

This text is considered a comprehensive reference for statistical approaches to natural language processing, suitable for both teaching and professional use. The reviewer commends its depth and breadth, making it a valuable resource in the field.

KB Cohen's review on Project MUSE emphasizes the book's role as a comprehensive reference text. They note that the book is particularly useful for those teaching courses or working in the field of natural language processing. The depth and breadth of the content are praised, making it a go-to resource for anyone looking to understand the statistical approaches in NLP. The reviewer suggests that the book's thorough coverage and rigorous treatment of the subject matter make it an essential addition to any NLP practitioner's library.

Quick quotes

    This is a comprehensive reference text on statistical approaches to natural language processing

    As such, anyone teaching courses or employed in that field will find it invaluable

    It is a valuable resource in the field

Goodreads · 2000-01-01
valuable 4.10

The book is highly regarded for its thorough coverage of the theory and algorithms necessary for building NLP tools. It is praised for its rigorous approach to both mathematical and linguistic theories.

A Goodreads reviewer highlights the book's extensive coverage of the theory and algorithms essential for NLP tool development. They appreciate the rigorous approach to both mathematical and linguistic theories, making it a valuable resource for those interested in the field. The reviewer notes that the book's detailed treatment of these topics makes it a standout in the realm of NLP literature. The book is seen as a must-read for anyone looking to build a strong foundation in statistical NLP, providing both the theoretical background and practical algorithms needed for effective tool development.

Quick quotes

    The book contains all the theory and algorithms needed for building NLP tools

    It provides broad but rigorous coverage of mathematical and linguistic theories

    The Manning and Schutze book is much more mathematically oriented and goes into more detail on algorithms

Cornell University Computer Science · L Lee · 1999-01-01
comprehensive 4.50

The book is praised for its comprehensive coverage of statistical NLP, avoiding a one-size-fits-all approach to mathematical tools and theories. It is noted for its detailed exploration of algorithms and rigorous mathematical foundations.

The reviewer from Cornell University highlights the book's strength in providing a thorough and varied approach to statistical NLP. They appreciate the authors' decision to present the subject without forcing a homogeneous mathematical framework, which allows for a more nuanced understanding. The book is seen as a valuable resource for those interested in the theoretical underpinnings of NLP, particularly in its detailed treatment of algorithms and mathematical rigor. The reviewer suggests that this book is ideal for readers who want to delve deeply into the statistical aspects of NLP, rather than those looking for a superficial overview.

Quick quotes

    In organizing the book, the authors have ``decided against attempting to present Statistical NLP as homogeneous in terms of mathematical tools and theories

    The book contains all the theory and algorithms needed for building NLP tools

    It provides broad but rigorous coverage of mathematical and linguistic theories

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