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Statistical Language Learning
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Fler böcker av Eugene Charniak
Artificial Intelligence Programming
Eugene Charniak, Christopher K Riesbeck, Drew V McDermott, James R Meehan
Artificial intelligence research has thrived in the years since this best-selling AI classic was first published. The revision encompasses these advances by adapting its coding to Common Lisp, the well-documented language standard, and by bringing...
Coarse-to-Fine Natural Language Processing
Slav Petrov, Eugene Charniak
The impact of computer systems that can understand natural language will be tremendous. To develop this capability we need to be able to automatically and efficiently analyze large amounts of text. Manually devised rules are not sufficient to prov...
Recensioner i media
"This is a lovely book." -- David Nye
Bloggat om Statistical Language Learning
Part 1 The Standard Model: Two Technologies; Morphology and Knowledge of Words; Syntax and Context-Free Grammars; Chart Parsing; Meaning and Semantic Processing; Exercises. Part 2 Statistical Models and the Entropy of English: A Fragment of Probability Theory; Statistical Models; Speech Recognition; Entropy; Markov Chains; Cross Entropy; Cross Entropy as a Model Evaluator; Exercises. Part 3 Hidden Markov Models and Two Applications: Trigram Models of English; Hidden Markov Models; Part-of-Speech Tagging; Exercises. Part 4 Algorithms for Hidden Markov Models: Finding the Most Likely Path; Computing HMM Output Probabilities; HMM Training; Exercises. Part 5 Probabilistic Context-Free Grammars: Probabilistic Grammars; PCFGs and Syntactic Ambiguity; PCFGs and Grammar Induction; PCFGs and Ungrammaticality; PCFGs and Language Modelling; Basic Algorithms for PCFGs; Exercises. Part 6 The Mathematics of PCFGs: Relation of HMMs to PCFGs; Finding Sentence Probabilities for PCFGs; Training PCFGs; Exercises. Part 7 Learning Probabilistic Grammars: Why the Simple Approach Fails; Learning Dependency Grammars; Learning from a Bracketed Corpus; Improving a Partial Grammar; Exercises. Part 8 Syntactic Disambiguation: Simple Methods for Prepositional Phrases; Using Semantic Information; Relative-Clause Attachment; Uniform Use of Lexical/Semantic Information; Exercises. Part 9 Word Classes and Meaning: Clustering; Clustering by Next Word; Clustering with Syntactic Information; Problems with Word Clustering; Exercises. Part 10 Word Senses and Their Disambiguation: Word Senses Using Outside Information; Word Senses Without Outside Information; Meanings and Selectional Restrictions; Discussion; Exercises.