1. CS4705 Natural Language Processing
Midterm Review
CS4705
Natural Language Processing

2. Midterm Review Statistical v. Symbolic Processing Regular Expressions
80/20 Rule
Regular Expressions
Finite State Automata
Determinism v. non-determinism
(Weighted) Finite State Transducers
Morphology
Word Classes
Inflectional v. Derivational
Affixation, infixation, concatenation
Morphotactics

3. Morphological parsing
Koskenniemi’s two-level morphology
Porter stemmer
Minimum Edit Distance (Levenshtein)
N-grams
Markov assumption
Chain Rule
Language Modeling
Simple, Adaptive, Class-based (syntax-based), bursty
Smoothing
Add-one, Witten-Bell, Good-Turing
Back-off
Perplexity, Entropy
Maximum Likelihood Estimation

4. Syntax Context Free Grammars
Chomsky’s view: Syntax is cognitive reality
Parse Trees
Dependency Structure
Part-of-Speech Tagging
Hand Written Rules v. Statistical v. Hybrid
Brill Tagging
Types of Ambiguity
Context Free Grammars
Top-down v. Bottom-up Derivations
Left Corners
Grammar Equivalence
Normal Forms (CNF)

5. Probabilistic Parsing
(p)CYK, Earley Parsing
Derivational Probability
Lexicalization
Classification
Supertagging
Machine Learning
Dependent v. Independent variables
Training v. Development Test v. Test sets
Feature Vectors
Metrics
Accuracy
Precision, Recall, F-Measure
Gold Standards

6. Semantics Meaning Representations
Semantic Roles, Subcategorization frames
FOPC
Pros
Cons
Temporal Representations
Richenbach
Aspect
Beliefs, Desires, Intention Representation
Syntax-driven semantics