Python自然语言处理 英文版2025|PDF|Epub|mobi|kindle电子书版本百度云盘下载

Python自然语言处理 英文版PDF格式电子书版下载

注意：本站所有压缩包均有解压码： 点击下载压缩包解压工具

1．Language Processing and Python1

1.1 Computing with Language:Texts and Words1

1.2 A Closer Look at Python:Texts as Lists of Words10

1.3 Computing with Language:Simple Statistics16

1.4 Back to Python:Making Decisions and Taking Control22

1.5 Automatic Natural Language Understanding27

1.6 Summary33

1.7 Further Reading34

1.8 Exercises35

2．Accessing Text Corpora and Lexical Resources39

2.1 Accessing Text Corpora39

2.2 Conditional Frequency Distributions52

2.3 More Python:Reusing Code56

2.4 Lexical Resources59

2.5 WordNet67

2.6 Summary73

2.7 Further Reading73

2.8 Exercises74

3．Processing Raw Text79

3.1 Accessing Text from the Web and from Disk80

3.2 Strings:Text Processing at the Lowest Level87

3.3 Text Processing with Unicode93

3.4 Regular Expressions for Detecting Word Patterns97

3.5 Useful Applications of Regular Expressions102

3.6 Normalizing Text107

3.7 Regular Expressions for Tokenizing Text109

3.8 Segmentation112

3.9 Formatting:From Lists to Strings116

3.10 Summary121

3.11 Further Reading122

3.12 Exercises123

4．Writing Structured Programs129

4.1 Back to the Basics130

4.2 Sequences133

4.3 Questions of Style138

4.4 Functions:The Foundation of Structured Programming142

4.5 Doing More with Functions149

4.6 Program Development154

4.7 Algorithm Design160

4.8 A Sample of Python Libraries167

4.9 Summary172

4.10 Further Reading173

4.11 Exercises173

5．Categorizing and Tagging Words179

5.1 Using a Tagger179

5.2 Tagged Corpora181

5.3 Mapping Words to Properties Using Python Dictionaries189

5.4 Automatic Tagging198

5.5 N-Gram Tagging202

5.6 Transformation-Based Tagging208

5.7 How to Determine the Category of a Word210

5.8 Summary213

5.9 Further Reading214

5.10 Exercises215

6．Learning to Classify Text221

6.1 Supervised Classifcation221

6.2 Further Examples of Supervised Classification233

6.3 Evaluation237

6.4 Decision Trees242

6.5 Naive Bayes Classifiers245

6.6 Maximum Entropy Classifiers250

6.7 Modeling Linguistic Patterns254

6.8 Summary256

6.9 Further Reading256

6.10 Exercises257

7．Extracting Information from Text261

7.1 Information Extraction261

7.2 Chunking264

7.3 Developing and Evaluating Chunkers270

7.4 Recursion in Linguistic Structure277

7.5 Named Entity Recognition281

7.6 Relation Extraction284

7.7 Summary285

7.8 Further Reading286

7.9 Exercises286

8．Analyzing Sentence Structure291

8.1 Some Grammatical Dilemmas292

8.2 What's the Use of Syntax?295

8.3 Context-Free Grammar298

8.4 Parsing with Context-Free Grammar302

8.5 Dependencies and Dependency Grammar310

8.6 Grammar Development315

8.7 Summary321

8.8 Further Reading322

8.9 Exercises322

9．Building Feature-Based Grammars327

9.1 Grammatical Features327

9.2 Processing Feature Structures337

9.3 Extending a Feature-Based Grammar344

9.4 Summary356

9.5 Further Reading357

9.6 Exercises358

10．Analyzing the Meaning of Sentences361

10.1 Natural Language Understanding361

10.2 Propositional Logic368

10.3 First-Order Logic372

10.4 The Semantics of English Sentences385

10.5 Discourse Semantics397

10.6 Summary402

10.7 Further Reading403

10.8 Exercises404

11．Managing Linguistic Data407

11.1 Corpus Structure:A Case Study407

11.2 The Life Cycle of a Corpus412

11.3 Acquiring Data416

11.4 Working with XML425

11.5 Working with Toolbox Data431

11.6 Describing Language Resources Using OLAC Metadata435

11.7 Summary437

11.8 Further Reading437

11.9 Exercises438

Afterword:The Language Challenge441

Bibliography449

NLTK Index459

General Index463