CS4705 Natural Language Processing. Regular Expressions Finite State Automata ◦ Determinism v. non-determinism ◦ (Weighted) Finite State Transducers.
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Presentation on theme: "CS4705 Natural Language Processing. Regular Expressions Finite State Automata ◦ Determinism v. non-determinism ◦ (Weighted) Finite State Transducers."— Presentation transcript:
Creating and using ngram LMs ◦ Corpora ◦ Maximum Likelihood Estimation Syntax ◦ Chomsky’s view: Syntax is cognitive reality ◦ Parse Trees Dependency Structure ◦ What is a good parse tree? ◦ Part-of-Speech Tagging Hand Written Rules v. Statistical v. Hybrid Brill Tagging HMMs
◦ Types of Ambiguity Context Free Grammars ◦ Top-down v. Bottom-up Derivations Early Algorithm ◦ Grammar Equivalence ◦ Normal Forms (CNF) ◦ Modifying the grammar Probabilistic Parsing ◦ Derivational Probability ◦ Computing probabilities for a rule ◦ Choosing a rule probabilistically ◦ Lexicalization
Machine Learning ◦ Dependent v. Independent variables ◦ Training v. Development Test v. Test sets ◦ Feature Vectors ◦ Metrics Accuracy Precision, Recall, F-Measure ◦ Gold Standards Semantics ◦ Where it fits ◦ Thematic roles ◦ First Order Predicate Calculus as a representation ◦ Semantic Analysis will not be covered on the midterm