TEXT MINING APPLICATION PROGRAMMING
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1 TEXT MINING APPLICATION PROGRAMMING MANU KONCHADY CHARLES RIVER MEDIA Boston, Massachusetts
2 Contents Preface Acknowledgments xv xix Introduction 1 Originsof Text Mining 4 Information Retrieval 4 Natural Language Processing 5 Understanding Text 7 Polysemy 8 Synonymy 9 Applications 11 Business 11 Mediane and Law 16 Society 18 Information Visualization 20 An Architecture for Text Mining Applications 21 Text Mining Functions 23 A Layered Model 25 Text Mine Installation 27 Software 27 Usage 28 Summary 29 References 30 VII
3 VÜi Contents - Mathematics Background 31 Probability 34 Least Squares Method 36 Entropy 37 Related-Event Probabilities 38 Bayes's Rule 40 Probability Distributions 42 Binomial Distribution 42 Poisson Distribution 45 Normal Distribution 47 Sampling Distributions 48 T-Distribution 50 Estimation 51 Expectation Maximization Algorithm 52 Hypothesis Testing 55 Chi-Square Test 56 Matrices 58 Singular Value Decomposition 60 Summary 62 References 62 Exploring Text 63 Words 65 Token Assembly 67 Word Sterns 72 Base Words 73 Word and Meaning Relationships 74 Patterns in Words and Letters 76 Word Statistics 80 Zipf's Law 84
4 Contents IX Sentences 88 Indexing Document Text 91 Frequency-Based 93 Stopwords 96 Inverse Document Frequency 97 Latent Semantic Indexing 100 Summary 110 References Markov Models and POS Tagging 113 Hidden Markov Models 118 Observation Probability 119 State Sequence 121 Parameter Estimation 123 POS Taggers 126 HMM Taggers 128 Rule-Based Taggers 131 Training a Tagger 137 Building a Tagger 140 Word Sense Disambiguation 144 An Implementation of a WSD 145 Evaluation ofwsds 148 Summary 149 References Information Extraction 151 IE Applications 152 Entity Extraction 156 HMMs for Entity Extraction 158 Implementation of an Entity Extractor 162
5 X Contents IE Systems 170 Fastus 172 Rapier 175 Phrase Extraction 178 Summary 181 References 182 Search Engines 183 Early Search Engines 184 Medline 185 Dialog 186 Indexing Text for Search 187 An Implementation in Text Mine 189 Google Index 192 Indexing Multimedia 194 Queries 197 Boolean Queries 198 Multimedia Queries 198 Relevance Feedback 200 Searching an Index 202 Searching in Text Mine 203 Google Search 204 Evaluation 205 Ranking Algorithms 209 Link Structure of Web Pages 210 Viewing Search Results 218 Summary 221 References 222
6 Contents XI 7 Searching the Web 225 Web Structure 226 Search Engine Coverage 229 Web Directories 233 A Distributed Search 234 Web Communities 236 The Hidden Web 238 Crawlers 241 Web Search Engine Crawlers 242 Focused Crawlers 247 Text Mine Crawler 252 Crawl Visualization 258 Summary 260 References Clustering Documents 263 Cluster Organization 265 Cluster Parameters 267 Cluster-Based Search 267 Searching with a Taxonomy 268 Similarity Measures 269 Linking Methods 271 Clustering Methods 272 K-Means 276 Simulated Annealing 279 Genetic Algorithms 282 Scatter/Gather 285 Visual Tools for Clusters 287 Cluster Evaluation 289 Summary 297 References 297
7 XII Contents 9 Text Categorization 299 Categorization Problem 300 Filtering 302 A Bayesian Filter 305 Features of Spam 307 Requirements for a Spam Detector 309 An Archive 309 Categorization 311 Monitor 313 Personal Network 314 Chain 315 Categorization Methods 317 Rocchio's Algorithm 318 Perceptrons 319 Decision Trees 321 Nearest Neighbor 323 Support Vector Machines 325 Summary 330 References Summarization 333 Training a Summarizer 335 Sentence Selection 337 News Articles 338 Threads 339 Web Pages 342 A Cluster-Based Summarizer 345 Implementation ofa Summarizer 349 Evaluation of Summaries 352
8 Contents Information Monitor 354 Event Detection 355 Event Tracking 357 Monitoring the News 357 Sentiment Analysis 362 Summary 365 References Question & Answer 367 Question Classification 369 Implementation of a Question Classifier 371 A Natural Language FAQ 377 Reading Comprehension 379 Local Q&A 383 Murax 383 TREC 385 Web Q&A 386 AnswerBus 387 NSIR 389 Computer-Aided Q&A 394 Finding Experts 394 Summary 395 References 396 About the CD-ROM 399 Text Mine 399 Installation 399 Database Management 401 Security 401 Testing 401
9 Contents Tools 402 Sources 402 WordNet 403 Reuters 403 SVDPACKC 403 Lists 403 Index 405
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