Python自然语言处理

Preface

1.Language Processing and Python

1.1 Computing with Language： Texts and Wor...

Preface

1.Language Processing and Python

1.1 Computing with Language： Texts and Words

1.2 A Closer Look at Python： Texts as Lists of Words

1.3 Computing with Language： Simple Statistics

1.4 Back to Python： Making Decisions and Taking Control

1.5 Automatic Natural Language Understanding

1.6 Summary

1.7 Further Reading

1.8 Exercises

2.Accessing Text Corpora and Lexical Resources

2.1 Accessing Text Corpora

2.2 Conditional Frequency Distributions

2.3 More Python： Reusing Code

2.4 Lexical Resources

2.5 WordNet

2.6 Summary

2.7 Further Reading

2.8 Exercises

3.Processing Raw Text

3.1 Accessing Text from the Web and from Disk

3.2 Strings： Text Processing at the Lowest Level

3.3 Text Processing with Unicode

3.4 Regular Expressions for Detecting Word Patterns

3.5 Useful Applications of Regular Expressions

3.6 Normalizing Text

3.7 Regular Expressions for Tokenizing Text

3.8 Segmentation

3.9 Formatting： From Lists to Strings

3.10 Summary

3.11 Further Reading

3.12 Exercises

4.Writing Structured Programs

4.1 Back to the Basics

4.2 Sequences

4.3 Questions of Style

4.4 Functions： The Foundation of Structured Programming

4.5 Doing More with Functions

4.6 Program Development

4.7 Algorithm Design

4.8 A Sample of Python Libraries

4.9 Summary

4.10 Further Reading

4.11 Exercises

5.Categorizing andTagging Words

5.1 Using a Tagger

5.2 Tagged Corpora

5.3 Mapping Words to Properties Using Python Dictionaries

5.4 Automatic Tagging

5.5 N-Gram Tagging

5.6 Transformation-Based Tagging

5.7 How to Determine the Category of a Word

5.8 Summary

5.9 Further Reading

5.10 Exercises

6.Learning to Classify Text

6.1 Supervised Classification

6.2 Further Examples of Supervised Classification

6.3 Evaluation

6.4 Decision Trees

6.5 Naive Bayes Classifiers

6.6 Maximum Entropy Classifiers

6.7 Modeling Linguistic Patterns

6.8 Summary

6.9 Further Reading

6.10 Exercises

7.Extracting Information from Text

7.1 Information Extraction

7.2 Chunking

7.3 Developing and Evaluating Chunkers

7.4 Recursion in Linguistic Structure

7.5 Named Entity Recognition

7.6 Relation Extraction

7.7 Summary

7.8 Further Reading

7.9 Exercises

8.Analyzing Sentence Structure

8.1 Some Grammatical Dilemmas

8.2 Whats the Use of Syntax?

8.3 Context-Free Grammar

8.4 Parsing with Context-Free Grammar

8.5 Dependencies and Dependency Grammar

8.6 Grammar Development

8.7 Summary

8.8 Further Reading

8.9 Exercises

9.Building Feature-Based Grammars

9.1 Grammatical Features

9.2 Processing Feature Structures

9.3 Extending a Feature-Based Grammar

9.4 Summary

9.5 Further Reading

9.6 Exercises

10.Analyzing the Meaning of Sentences

10.1 Natural Language Understanding

10.2 Propositional Logic

10.3 First-Order Logic

10.4 The Semantics of English Sentences

10.5 Discourse Semantics

10.6 Summary

10.7 Further Reading

10.8 Exercises

11.Managing Linguistic Data

11.1 Corpus Structure： A Case Study

11.2 The Life Cycle of a Corpus

11.3 Acquiring Data

11.4 Working with XML

11.5 Working with Toolbox Data

11.6 Describing Language Resources Using OLAC Metadata

11.7 Summary

11.8 Further Reading

11.9 Exercises

Afterword： The Language Challenge

Bibliography

NLTK Index

General Index