Foundations of statistical natural language processing

Foundations of statistical natural language processing

by Christopher D. Manning, Hinrich Schütze

1999
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Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications. - [Source][1] [1]: http://books.google.com/books?id=YiFDxbEX3SUC&source=gbs_ViewAPI

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  1. 1

    How has the transition from rule-based linguistics to statistical modeling fundamentally changed how we understand human language and communication?

  2. 2

    Considering the mathematical rigor required in this text, how does translating human nuance and ambiguity into probability distributions alter our appreciation of poetry, literature, or everyday speech?

  3. 3

    When you encounter predictive text, machine translation, or large language models today, how does understanding the foundational statistical methods in this book change your perception of their "intelligence"?

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