Foundations of Statistical Natural Language Processing

Manning C.D., Schütze H.0026213360

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.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.”

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Table of contents :
Cover……Page 1
Brief Contents……Page 3
Contents……Page 4
Table of Notations……Page 21
Preface……Page 24
Road Map……Page 29
Part I. Preliminaries……Page 32
Introduction……Page 34
Mathematical Foundations……Page 69
Linguistic Essentials……Page 111
Corpus-Based Work……Page 146
Part II. Words……Page 177
Collocations……Page 179
Statistical Inference: n-gram Models over Sparse Data……Page 218
Word Sense Disambiguation……Page 255
Lexical Acquisition……Page 290
Part III. Grammar……Page 340
Markov Models……Page 341
Part-of-Speech Tagging……Page 366
Probabilistic Context Free Grammars……Page 406
Probabilistic Parsing……Page 431
Part IV. Applications and Techniques……Page 486
Statistical Alignment and Machine Translation……Page 488
Clustering……Page 520
Topics in In formation RetrievaI……Page 554
Text Categorization……Page 600
Tiny Statistical Tables……Page 634
Bibliography……Page 636
Index……Page 681