Foundations of Statistical Natural Language Processing

Front Cover
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.
 

Contents

Introduction
3
60
24
Mathematical Foundations
39
Linguistic Essentials
81
78
114
CorpusBased Work
117
Collocations
151
ngram Models over Sparse Data
191
PartofSpeech Tagging
341
Probabilistic Context Free Grammars
381
Probabilistic Parsing
407
Statistical Alignment and Machine Translation
463
Clustering
495
Topics in Information Retrieval
529
Text Categorization
575
Text Categorization
607

Word Sense Disambiguation
229
Word Sense Disambiguation
259
Lexical Acquisition
265
Markov Models
317
Tiny Statistical Tables
609
Index
620
192
637
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