Python 3 Text Processing with NLTK 3 Cookbook

封面

版权页

Credits

About the Author

About the Reviewers

www.PacktPub.com

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Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Chapter 1. Tokenizing Text and WordNet Basics

Introduction

Tokenizing text into sentences

Tokenizing sentences into words

Tokenizing sentences using regular expressions

Training a sentence tokenizer

Filtering stopwords in a tokenized sentence

Looking up Synsets for a word in WordNet

Looking up lemmas and synonyms in WordNet

Calculating WordNet Synset similarity

Discovering word collocations

Chapter 2. Replacing and Correcting Words

Introduction

Stemming words

Lemmatizing words with WordNet

Replacing words matching regular expressions

Removing repeating characters

Spelling correction with Enchant

Replacing synonyms

Replacing negations with antonyms

Chapter 3. Creating Custom Corpora

Introduction

Setting up a custom corpus

Creating a wordlist corpus

Creating a part-of-speech tagged word corpus

Creating a chunked phrase corpus

Creating a categorized text corpus

Creating a categorized chunk corpus reader

Lazy corpus loading

Creating a custom corpus view

Creating a MongoDB-backed corpus reader

Corpus editing with file locking

Chapter 4. Part-of-speech Tagging

Introduction

Default tagging

Training a unigram part-of-speech tagger

Combining taggers with backoff tagging

Training and combining ngram taggers

Creating a model of likely word tags

Tagging with regular expressions

Affix tagging

Training a Brill tagger

Training the TnT tagger

Using WordNet for tagging

Tagging proper names

Classifier-based tagging

Training a tagger with NLTK-Trainer

Chapter 5. Extracting Chunks

Introduction

Chunking and chinking with regular expressions

Merging and splitting chunks with regular expressions

Expanding and removing chunks with regular expressions

Partial parsing with regular expressions

Training a tagger-based chunker

Classification-based chunking

Extracting named entities

Extracting proper noun chunks

Extracting location chunks

Training a named entity chunker

Training a chunker with NLTK-Trainer

Chapter 6. Transforming Chunks and Trees

Introduction

Filtering insignificant words from a sentence

Correcting verb forms

Swapping verb phrases

Swapping noun cardinals

Swapping infinitive phrases

Singularizing plural nouns

Chaining chunk transformations

Converting a chunk tree to text

Flattening a deep tree

Creating a shallow tree

Converting tree labels

Chapter 7. Text Classification

Introduction

Bag of words feature extraction

Training a Naive Bayes classifier

Training a decision tree classifier

Training a maximum entropy classifier

Training scikit-learn classifiers

Measuring precision and recall of a classifier

Calculating high information words

Combining classifiers with voting

Classifying with multiple binary classifiers

Training a classifier with NLTK-Trainer

Chapter 8. Distributed Processing and Handling Large Datasets