Natural Language Processing

CSC544, Fall 2002

Prof. Eduard Hovy and Prof. Daniel Marcu

Tu/Th 2:00-3:20, VHE 210

Textbooks:

Syllabus

Parsing:

[Marcu]

Aug 27

Introduction to NLP and Parsing

[Marcu]

Aug 29

Efficient Parsing: The Chart Parsing Algorithm
  - Assignment 1 out

[Marcu]

Sept 3

Probabilistic/Stochastic Parsing Models: Probabilistic  Context Free Grammars

[Marcu]

Sept 5

Probabilistic/Stochastic Parsing Models: History-based  Models (1)

[Marcu]

Sept 10

Probabilistic/Stochastic Parsing Models: History-based  Models (2)

[Marcu]

Sept 12

Discourse Parsing

Semantics:

 

 

[Marcu]

Sept 17

Introduction to Semantics: Theories of Meaning
Knowledge Representation Formalisms for Natural Language

[Marcu]

Sept 19

The Relation Between Syntax and Semantics

[Marcu]

Sept 24

Shallow semantics in current NLP applications

Statistical NLP:

 

 

[Marcu]

Sept 26

Supervised Learning Methods Applied to NLP

[Marcu]

Oct 1

Bootstrapping Methods Applied to NLP
   - Assignment 1 due
   - Assignment 2 out

[Marcu]

Oct 3

Unsupervised Learning Methods Applied to NLP

[Marcu]

Oct 8

Unsupervised Learning Methods Applied to NLP

[Marcu]

Oct 10

Designing Experiments and Evaluating Hypotheses

 Generation:

 

 

[Hovy]

Oct 15

Knowledge Representation for NLP

[Hovy]

Oct 17

Knowledge Representation for NLP

[Hovy]

Oct 22

free

[Hovy]

Oct 24

Realization 1: Templates and Phrasal Generation 

[Hovy]

Oct 29

Realization 2: Feature-Based Generation 

[Hovy]

Oct 31

Text Planning 1: Text Structure and Schemas
    - Assignment 2 due
    - Assignment 3 out

[Hovy]

Nov 5

 Text Planning 2: RST and Text Plans 

Applications:

 

 

[Hovy]

Nov 7

Microplanning

[Hovy]

Nov 12

Generator Control through Pragmatics 

[Hovy]

Nov 14

Machine Translation 1: Theory and Symbolic Methods

[Hovy]

Nov 19

Machine Translation 2: Statistical Methods

[Hovy, Marcu]

Nov 21

Text Summarization and Question Answering

[Hovy]

Nov 26

Speech Recognition
   - Assignment 3 due
   - Take-home Exam out

[Oard]

Dec 3

Information Retrieval

[Leuski]

Dec 5

Interfaces for NLP Systems
   - Take-home Exam due

Grading

There will be 3 assignments, each worth 30% of the final mark. The final will be an essay style take-home exam, worth 10% of the total mark.