2009 NaturalLanguageProcessingwithPy
- (Bird et al., 2009) ⇒ Steven Bird, Ewan Klein, and Edward Loper. (2009). “Natural Language Processing with Python.” O'Reilly Media. ISBN:9780596555719
Subject Headings: NLTK Python Toolkit, Linguistic Resource, Text Classification, Information Extraction System.
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Abstract
This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication.
Packed with examples and exercises, Natural Language Processing with Python will help you:
- Extract information from unstructured text, either to guess the topic or identify "named entities".
- Analyze linguistic structure in text, including parsing and semantic analysis
- Access popular linguistic databases, including WordNet and treebanks
- Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence
This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.
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Chapter 1 Language Processing and Python
Computing with Language: Texts and Words
A Closer Look at Python: Texts as Lists of Words
Computing with Language: Simple Statistics
Back to Python: Making Decisions and Taking Control
Automatic Natural Language Understanding
Summary
Further Reading
Exercises
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Chapter 2 Accessing Text Corpora and Lexical Resources
Accessing Text Corpora
Conditional Frequency Distributions
More Python: Reusing Code
Lexical Resources
WordNet
Summary
Further Reading
Exercises
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Chapter 3 Processing Raw Text
Accessing Text from the Web and from Disk
Strings: Text Processing at the Lowest Level
Text Processing with Unicode
Regular Expressions for Detecting Word Patterns
Useful Applications of Regular Expressions
Normalizing Text
Regular Expressions for Tokenizing Text
Segmentation
Formatting: From Lists to Strings
Summary
Further Reading
Exercises
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Chapter 4 Writing Structured Programs
Back to the Basics
Sequences
Questions of Style
Functions: The Foundation of Structured Programming
Doing More with Functions
Program Development
Algorithm Design
A Sample of Python Libraries
Summary
Further Reading
Exercises
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Chapter 5 Categorizing and Tagging Words
Using a Tagger
Tagged Corpora
Mapping Words to Properties Using Python Dictionaries
Automatic Tagging
N-Gram Tagging
Transformation-Based Tagging
How to Determine the Category of a Word
Summary
Further Reading
Exercises
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Chapter 6 Learning to Classify Text
Supervised Classification
Further Examples of Supervised Classification
Evaluation
Decision Trees
Naive Bayes Classifiers
Maximum Entropy Classifiers
Modeling Linguistic Patterns
Summary
Further Reading
Exercises
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Chapter 7 Extracting Information from Text
Information Extraction
Chunking
Developing and Evaluating Chunkers
Recursion in Linguistic Structure
Named Entity Recognition
Relation Extraction
Summary
Further Reading
Exercises
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Chapter 8 Analyzing Sentence Structure
Some Grammatical Dilemmas
What’s the Use of Syntax?
Context-Free Grammar
Parsing with Context-Free Grammar
Dependencies and Dependency Grammar
Grammar Development
Summary
Further Reading
Exercises
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Chapter 9 Building Feature-Based Grammars
Grammatical Features
Processing Feature Structures
Extending a Feature-Based Grammar
Summary
Further Reading
Exercises
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Chapter 10 Analyzing the Meaning of Sentences
Natural Language Understanding
Propositional Logic
First-Order Logic
The Semantics of English Sentences
Discourse Semantics
Summary
Further Reading
Exercises
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Chapter 11 Managing Linguistic Data
Corpus Structure: A Case Study
The Life Cycle of a Corpus
Acquiring Data
Working with XML
Working with Toolbox Data
Describing Language Resources Using OLAC Metadata
Summary
Further Reading
Exercises
Appendix Afterword: The Language Challenge
Language Processing Versus Symbol Processing
Contemporary Philosophical Divides
NLTK Roadmap
References
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| Author | volume | Date Value | title | type | journal | titleUrl | doi | note | year | |
|---|---|---|---|---|---|---|---|---|---|---|
| 2009 NaturalLanguageProcessingwithPy | Ewan Klein Steven Bird Edward Loper | Natural Language Processing with Python | 2009 |