Foundations of Statistical Natural Language Processing
Douban
Christopher D. Manning / Hinrich Schütze
overview
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
Mathematical Foundations
Linguistic Essentials
Corpus-Based Work
Collocations
Statistical Inference: n-gram Models over Sparse Data
Word Sense Disambiguation
Lexical Acquisition
Markov Models
Part-of-Speech Tagging
Probabilistic Context Free Grammars
Probabilistic Parsing
Statistical Alignment and Machine Translation
Clustering
Topics in Information Retrieval
Text Categorization
