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
4
6
5
22
Mathematical Foundations
39
2
59
1
77
Linguistic Essentials
81
2
86
ngram Models over Sparse Data
191
Word Sense Disambiguation
229
Lexical Acquisition
265
Markov Models
317
PartofSpeech Tagging
341
Probabilistic Context Free Grammars
381
Probabilistic Parsing
407
Statistical Alignment and Machine Translation
463

84
115
CorpusBased Work
117
Different formats for telephone numbers appearing in
131
Sentence lengths in newswire text
137
Collocations
151
1
153
Clustering
495
Topics in Information Retrieval
529
Text Categorization
575
Tiny Statistical Tables
609
Index
657
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