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Jun 1999
ISBN 0262133601
620 pp.
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Foundations of Statistical Natural Language Processing
Christopher D. Manning and Hinrich Schütze

"Statistical natural-language processing is, in my estimation, one of the most fast-moving and exciting areas of computer science these days. Anyone who wants to learn this field would be well advised to get this book. For that matter, the same goes for anyone who is already in the field. I know that it is going to be one of the most well-thumbed books on my bookshelf."
-- Eugene Charniak, Department of Computer Science, Brown University

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.

More on this book

Table of Contents
 List of Tables
 List of Figures
 Table of Notations
 Preface
 Road Map
I Preliminaries
1 Introduction
2 Mathematical Foundations
3 Linguistics Essentials
4 Corpus-Based Work
II Words
5 Collocations
6 Statistical Inference: n-gram Models over Sparse Data
7 Word Sense Disambiguation
8 Lexical Acquisition
III Grammar
9 Markov Models
10 Part-of-Speech Tagging
11 Probabilistic Context Free Grammars
12 Probabilistic Parsing
IV Applications and Techniques
13 Statistical Alignment and Machine Translation
14 Clustering
15 Topics in Information Retrieval
16 Text Categorization
 Tiny Statistical Tables
 Bibliography
 Index
 
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Related Topics
Computing
Linguistics, Language


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