CS 4705: Introduction to Natural Language Processing, Fall 2007
Time:	TTh: 2:40-3:55	Place	327 Mudd
Professor:	Julia Hirschberg	Office Hours:	Tu 4-5,We 10-11
Email:	julia@cs.columbia.edu	Phone:	212-939-7114
Teaching Assistant:	Frank Enos	Office Hours:	Tu/Th 1-2
Email:	frank@cs.columbia.edu	Phone:	212-939-7193

Announcements || Academic Integrity ||  Contributions || Description
Links to Resources || Requirements || Syllabus || Text

Announcements:

1. Check Columbia Courseworks for announcements, your grades (only you will see them), and discussion. Professor Hirschberg and your TA will monitor the discussion lists to answer questions.
2. If you are interested in doing NLP research projects for credit, please let Professor Hirschberg know. The NLP group often has research opportunities available.  Other postings may be found at this location.

Description:

This course provides an introduction to the field of computational linguistics, aka natural language processing (NLP). We will learn how to create systems that can understand and produce language, for applications such as information extraction, machine translation, automatic summarization, question-answering, and interactive dialogue systems. The course will cover linguistic (knowledge-based) and statistical approaches to language processing in the three major subfields of NLP: syntax (language structures), semantics (language meaning), and pragmatics/discourse (the interpretation of language in context). Homework assignments will reflect research problems computational linguists currently work on, including analyzing and extracting information from large online corpora.

Textbook:

Speech and Language Processing by Jurafsky and Martin. It will be available from the University Bookstore, as well as from Amazon and other online providers. It should also be on reserve in the Engineering Library. Please check the online errata for the text for each chapter as you read it. 

Requirements:

Four homework assignments, a midterm and a final exam. Each student in the course is allowed a total of 4 late days on homeworks with no questions asked; after that, 10% per late day will be deducted from the homework grade, unless you have a note from your doctor.  Do not use these up early!  Save them for real emergencies. 

All students are required to have a Computer Science Account for this class. To sign up for one, go to the CRF website and then click on "Apply for an Account".

Homework submission procedure.

Academic Integrity:

Copying or paraphrasing someone's work (code included), or permitting your own work to be copied or paraphrased, even if only in part, is not allowed, and will result in an automatic grade of 0 for the entire assignment or exam in which the copying or paraphrasing was done. Your grade should reflect your own work. If you believe you are going to have trouble completing an assignment, please talk to the instructor or TA in advance of the due date.

Syllabus:

Week	Class	Topic	Reading	Assignments
1	Sep 4	Introduction and Course Overview
	Sep 6	Natural Language and Formal Language: Regular Expressions and Finite State Automata	Ch 1-2
2	Sep 11	Words and Their Parts:  Morphology	Ch 3.1
	Sep 13	Word Construction and Analysis: Morphological Parsing	Ch 3: 2-6	HW1 assigned; text inputs file1 and file2
3	Sep 18	Word Tokenization, Pronunciation and Spelling	Ch 5:1-8
	Sep 20	N-grams and Language Models	Ch 6
4	Sep 25	Word Classes and POS Tagging; Questions	Ch 8	HW1 due
	Sep 27	Machine Learning Approaches to NLP and Introduction to Weka	Jansche&Abney02	HW2 assigned; FAQ
5	Oct 2	Context-Free Grammars	Ch 9	Guest Speaker: Owen Rambow
	Oct 4	Parsing with Context Free Grammars	Ch 10
6	Oct 9	Probabilistic and Lexicalized Parsing	Ch 12 (Be sure to replace figure 12.3 with new version )
	Oct 11	Catching Up; Representing Meaning	Ch 14
7	Oct 16	Semantic Analysis and Midterm Review	Ch  15:1,4-6
	Oct 18	Midterm Examination	Sample midterm
	Oct 23	Relations Among Words	Ch 16:1-2
	Oct 25	WordsEye	Ch 16:3-5	Guest Speaker: Robert Coyne
8	Oct 30	Word Sense Disambiguation	Ch 17:1-2
	Nov 1	Information Retrieval and Information Extraction	Ch 17:3-5	HW2 due (2pm); how to submit
10	Nov 6	Holiday	Holiday	Holiday
	Nov 8	Pronouns and Reference Resolution	Ch 18: 18.1	HW3 assigned
	Nov 13	Algorithms for Reference Resolution
	Nov 15	Text Coherence and Discourse Structure	Ch 18.2-18.5; Grosz&Sidner86	Guest Speaker: Frank Enos
	Nov 20	Turn-taking and Grounding	Ch 19:1	Gust Speaker: Agustín Gravano
	Nov 22	Thanksgiving Holiday
13	Nov 27	Dialogue Systems	Ch19:2-6
	Nov 29	Summarization and Generation	Ch 20	HW3 due
14	Dec 4	Machine Translation	Ch 21	Guest Speaker: Nizar Habash
	Dec 6	Final Review
	Dec. 11-13			Study Days
	Dec. 14-21			Final Exams

Links to Resources (cf. also resources available from the text homepage):

General:

1. Karen Chung Language and Linguistics links
   
2. CatSpeak

Places to look up definitions and descriptions of terminology:

1. Oxford Dictionary of Linguistics
2. Interesting Language Factoids and Non

Chapters 1 and 2:

Try out one of the many versions of Eliza on the web.

Chapter3:

AT&T Labs - Research Finite State Machine Library

Later Chapters:

1. Appelt and Israel's information extraction tutorial (IJCAI-99).
2. Framenet.

Chapter 19:

1. Ask Jeeves -- a search engine that answers questions in plain English.
2. Answer Bus -- another Q/A system.
3. Columbia's NewsBlaster summarizer
4. IBM summarizer demo (canned)
5. Systran machine translation (also in use at Babelfish)
6. AT&T Labs - Research Finite State Machine Library
7. Michael Collins' Parser
8. On-line dictionaries in many languages.
9. WordNet
10. Framenet
11. CoBuildDirect Corpus
12. AT&T's SCANMail voicemail browsing/search system
13. DiaLeague 2001 -- includes a link to an online dialogue system demo.
14. James Allen's Dialogue Modeling for Spoken Language Systems ACL 1997 Tutorial
15. Festival speech synthesizer demo and links to other TTS systems
16. Julia Hirschberg's Intonational Variation in Spoken Dialogue Systems tutorial

Announcements || Academic Integrity || Contributions || Description
 Links to Resources|| Requirements || Syllabus || Text