Python 自然语言处理第二版（fix1）

Table of Contents......Page 3
Preface......Page 7
 Emphasis......Page 8
 Organization......Page 9
 Why Python?......Page 10
 Software Requirements......Page 11
 Natural Language Toolkit (NLTK)......Page 12
 For Instructors......Page 13
 Using Code Examples......Page 15
 How to Contact Us......Page 16
 Royalties......Page 17
 1.1  Computing with Language: Texts and Words......Page 19
  Getting Started with Python......Page 20
  Getting Started with NLTK......Page 21
  Searching Text......Page 22
  Counting Vocabulary......Page 25
  Lists......Page 28
  Indexing Lists......Page 30
  Variables......Page 32
  Strings......Page 33
 1.3  Computing with Language: Simple Statistics......Page 34
  Frequency Distributions......Page 35
  Fine-Grained Selection of Words......Page 37
  Collocations and Bigrams......Page 38
  Counting Other Things......Page 39
  Conditionals......Page 40
  Operating on Every Element......Page 42
  Nested Code Blocks......Page 43
  Looping with Conditions......Page 44
 1.5  Automatic Natural Language Understanding......Page 45
  Pronoun Resolution......Page 46
  Machine Translation......Page 47
  Spoken Dialogue Systems......Page 49
  Textual Entailment......Page 50
 1.6  Summary......Page 51
 1.7  Further Reading......Page 52
 1.8  Exercises......Page 53
 2.1  Accessing Text Corpora......Page 56
  Gutenberg Corpus......Page 57
  Brown Corpus......Page 59
  Reuters Corpus......Page 61
  Inaugural Address Corpus......Page 62
  Annotated Text Corpora......Page 63
  Corpora in Other Languages......Page 65
  Text Corpus Structure......Page 66
  Loading Your Own Corpus......Page 68
  Counting Words by Genre......Page 69
  Plotting and Tabulating Distributions......Page 70
  Generating Random Text with Bigrams......Page 72
  Creating Programs with a Text Editor......Page 73
  Functions......Page 74
 2.4  Lexical Resources......Page 76
  Wordlist Corpora......Page 77
  A Pronouncing Dictionary......Page 80
  Comparative Wordlists......Page 82
  Shoebox and Toolbox Lexicons......Page 83
  Senses and Synonyms......Page 84
  The WordNet Hierarchy......Page 86
  More Lexical Relations......Page 87
  Semantic Similarity......Page 88
 2.7  Further Reading......Page 90
 2.8  Exercises......Page 91
Chapter 3. Processing Raw Text......Page 95
  Electronic Books......Page 96
  Dealing with HTML......Page 97
  Processing Search Engine Results......Page 98
  Processing RSS Feeds......Page 99
  Reading Local Files......Page 100
  Capturing User Input......Page 101
  The NLP Pipeline......Page 102
  Basic Operations with Strings......Page 103
  Accessing Individual Characters......Page 105
  Accessing Substrings......Page 106
  The Difference Between Lists and Strings......Page 108
 3.3  Text Processing with Unicode......Page 109
  Extracting Encoded Text from Files......Page 110
 3.4  Regular Expressions for Detecting Word Patterns......Page 113
  Using Basic Metacharacters......Page 114
  Ranges and Closures......Page 115
  Doing More with Word Pieces......Page 118
  Finding Word Stems......Page 120
  Searching Tokenized Text......Page 121
  Stemmers......Page 123
  Lemmatization......Page 124
  Simple Approaches to Tokenization......Page 125
  Further Issues with Tokenization......Page 127
  Sentence Segmentation......Page 128
  Word Segmentation......Page 129
  From Lists to Strings......Page 132
  Strings and Formats......Page 133
  Lining Things Up......Page 134
  Text Wrapping......Page 136
 3.10  Summary......Page 137
 3.11  Further Reading......Page 138
 3.12  Exercises......Page 139
Chapter 4. Writing Structured Programs......Page 145
  Assignment......Page 146
  Equality......Page 148
 4.2  Sequences......Page 149
  Operating on Sequence Types......Page 150
  Combining Different Sequence Types......Page 152
  Generator Expressions......Page 153
  Python Coding Style......Page 154
  Procedural Versus Declarative Style......Page 155
  Some Legitimate Uses for Counters......Page 157
 4.4  Functions: The Foundation of Structured Programming......Page 158
  Function Inputs and Outputs......Page 159
  Parameter Passing......Page 160
  Variable Scope......Page 161
  Checking Parameter Types......Page 162
  Functional Decomposition......Page 163
  Documenting Functions......Page 164
  Functions As Arguments......Page 165
  Accumulative Functions......Page 166
  Higher-Order Functions......Page 167
  Named Arguments......Page 168
  Structure of a Python Module......Page 170
  Multimodule Programs......Page 171
  Sources of Error......Page 172
  Debugging Techniques......Page 174
  Defensive Programming......Page 175
  Recursion......Page 176
  Space-Time Trade-offs......Page 179
  Dynamic Programming......Page 181
 4.8  A Sample of Python Libraries......Page 183
  Matplotlib......Page 184
  NetworkX......Page 185
  csv......Page 186
  NumPy......Page 187
 4.9  Summary......Page 188
 4.11  Exercises......Page 189
 5.1  Using a Tagger......Page 194
  Reading Tagged Corpora......Page 196
  A Simplified Part-of-Speech Tagset......Page 198
  Nouns......Page 199
  Verbs......Page 200
  Adjectives and Adverbs......Page 201
  Exploring Tagged Corpora......Page 202
  Indexing Lists Versus Dictionaries......Page 204
  Dictionaries in Python......Page 205
  Default Dictionaries......Page 208
  Incrementally Updating a Dictionary......Page 209
  Complex Keys and Values......Page 211
  Inverting a Dictionary......Page 212
  The Default Tagger......Page 213
  The Regular Expression Tagger......Page 214
  The Lookup Tagger......Page 215
  Evaluation......Page 216
  Unigram Tagging......Page 217
  General N-Gram Tagging......Page 218
  Combining Taggers......Page 220
  Performance Limitations......Page 221
 5.6  Transformation-Based Tagging......Page 223
 5.7  How to Determine the Category of a Word......Page 225
  New Words......Page 226
  Morphology in Part-of-Speech Tagsets......Page 227
 5.8  Summary......Page 228
 5.9  Further Reading......Page 229
 5.10  Exercises......Page 230
 6.1  Supervised Classification......Page 235
  Gender Identification......Page 236
  Choosing the Right Features......Page 238
  Document Classification......Page 241
  Part-of-Speech Tagging......Page 243
  Exploiting Context......Page 244
  Sequence Classification......Page 245
  Sentence Segmentation......Page 247
  Recognizing Textual Entailment......Page 249
  The Test Set......Page 251
  Precision and Recall......Page 253
  Confusion Matrices......Page 254
  Cross-Validation......Page 255
 6.4  Decision Trees......Page 256
  Entropy and Information Gain......Page 257
 6.5  Naive Bayes Classifiers......Page 259
  Underlying Probabilistic Model......Page 261
  Zero Counts and Smoothing......Page 262
  The Naivete of Independence......Page 263
 6.6  Maximum Entropy Classifiers......Page 264
  The Maximum Entropy Model......Page 265
  Maximizing Entropy......Page 266
 6.7  Modeling Linguistic Patterns......Page 268
  What Do Models Tell Us?......Page 269
 6.9  Further Reading......Page 270
 6.10  Exercises......Page 271
 7.1  Information Extraction......Page 274
  Information Extraction Architecture......Page 276
  Noun Phrase Chunking......Page 277
  Chunking with Regular Expressions......Page 279
  Exploring Text Corpora......Page 280
  Chinking......Page 281
  Representing Chunks: Tags Versus Trees......Page 282
  Reading IOB Format and the CoNLL-2000 Chunking Corpus......Page 283
  Simple Evaluation and Baselines......Page 285
  Training Classifier-Based Chunkers......Page 287
  Building Nested Structure with Cascaded Chunkers......Page 290
  Trees......Page 292
  Tree Traversal......Page 293
 7.5  Named Entity Recognition......Page 294
 7.6  Relation Extraction......Page 297
 7.7  Summary......Page 298
 7.9  Exercises......Page 299
Chapter 8. Analyzing Sentence Structure......Page 303
  Linguistic Data and Unlimited Possibilities......Page 304
  Ubiquitous Ambiguity......Page 305
  Beyond n-grams......Page 307
  A Simple Grammar......Page 310
  Writing Your Own Grammars......Page 312
  Recursion in Syntactic Structure......Page 313
 8.4  Parsing with Context-Free Grammar......Page 314
  Recursive Descent Parsing......Page 315
  Shift-Reduce Parsing......Page 316
  The Left-Corner Parser......Page 318
  Well-Formed Substring Tables......Page 319
 8.5  Dependencies and Dependency Grammar......Page 322
  Valency and the Lexicon......Page 324
  Scaling Up......Page 326
  Treebanks and Grammars......Page 327
  Pernicious Ambiguity......Page 329
  Weighted Grammar......Page 330
 8.7  Summary......Page 333
 8.9  Exercises......Page 334
 9.1  Grammatical Features......Page 339
  Syntactic Agreement......Page 341
  Using Attributes and Constraints......Page 343
  Terminology......Page 347
 9.2  Processing Feature Structures......Page 349
  Subsumption and Unification......Page 353
  Subcategorization......Page 356
  Heads Revisited......Page 359
  Auxiliary Verbs and Inversion......Page 360
  Unbounded Dependency Constructions......Page 361
  Case and Gender in German......Page 365
 9.4  Summary......Page 368
 9.5  Further Reading......Page 369
 9.6  Exercises......Page 370
  Querying a Database......Page 373
  Natural Language, Semantics, and Logic......Page 377
 10.2  Propositional Logic......Page 380
  Syntax......Page 384
  First-Order Theorem Proving......Page 387
  Summarizing the Language of First-Order Logic......Page 388
  Truth in Model......Page 389
  Individual Variables and Assignments......Page 390
  Quantification......Page 392
  Quantifier Scope Ambiguity......Page 393
  Model Building......Page 395
  Compositional Semantics in Feature-Based Grammar......Page 397
  The λ-Calculus......Page 398
  Quantified NPs......Page 402
  Transitive Verbs......Page 403
  Quantifier Ambiguity Revisited......Page 406
  Discourse Representation Theory......Page 409
  Discourse Processing......Page 412
 10.6  Summary......Page 414
 10.7  Further Reading......Page 415
 10.8  Exercises......Page 416
  The Structure of TIMIT......Page 419
  Notable Design Features......Page 421
  Fundamental Data Types......Page 423
  Three Corpus Creation Scenarios......Page 424
  Quality Control......Page 425
  Curation Versus Evolution......Page 426
  Obtaining Data from Word Processor Files......Page 428
  Obtaining Data from Spreadsheets and Databases......Page 430
  Converting Data Formats......Page 431
  Deciding Which Layers of Annotation to Include......Page 432
  Standards and Tools......Page 433
  Special Considerations When Working with Endangered Languages......Page 434
  Using XML for Linguistic Structures......Page 437
  The Role of XML......Page 438
  The ElementTree Interface......Page 439
  Using ElementTree for Accessing Toolbox Data......Page 441
  Formatting Entries......Page 442
  Adding a Field to Each Entry......Page 443
  Validating a Toolbox Lexicon......Page 444
  OLAC: Open Language Archives Community......Page 447
 11.8  Further Reading......Page 449
 11.9  Exercises......Page 450
Afterword: The Language Challenge......Page 452
 Language Processing Versus Symbol Processing......Page 453
 Contemporary Philosophical Divides......Page 454
 NLTK Roadmap......Page 455
 Envoi.........Page 458
Bibliography......Page 459
NLTK Index......Page 469
General Index......Page 473