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Midterm Review

Midterm Review. CS4705 Natural Language Processing. Midterm Review. Regular Expressions Finite State Automata Determinism v. non-determinism (Weighted) Finite State Transducers Morphology Word Classes and POS Inflectional v. Derivational Affixation, infixation , concatenation

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Midterm Review

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  1. Midterm Review CS4705 Natural Language Processing

  2. Midterm Review • Regular Expressions • Finite State Automata • Determinism v. non-determinism • (Weighted) Finite State Transducers • Morphology • Word Classes and POS • Inflectional v. Derivational • Affixation, infixation, concatenation • Morphotactics • Different languages, different morphologies • Evidence from human performance

  3. Noisy channel model • Bayesian inference • N-grams • Markov assumption • Chain Rule • Language Modeling • Simple, Adaptive, Class-based (syntax-based) • Smoothing • Add-one, Witten-Bell, Good-Turing • Back-off models • Creating and using ngram LMs • Corpora • Maximum Likelihood Estimation

  4. Testing and Training • How to choose a corpus • How to divide • Part-of-Speech Tagging • Hand Written Rules v. Statistical v. Hybrid • Brill Tagging • HMMs • Syntax • Parse Trees • Constituent Structure vs. Dependency Structure • What is a good parse tree? • Types of Ambiguity

  5. Context Free Grammars • Top-down v. Bottom-up Derivations • Early Algorithm • Normal Forms (CNF) • Modifying the grammar • Probabilistic Parsing • Derivational Probability • Computing probabilities for a rule • Choosing a rule probabilistically • Lexicalized head driven grammars

  6. Semantics • Where it fits • Thematic roles • First Order Predicate Calculus as a representation • Compositional Semantics • Word relations • Word sense disambiguation • Naïve Bayes • Decision rules • Lesk simplified and corpus • Selectional restrictions

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