syllabus.

CS 4705: Introduction to Natural Language Processing, Fall 2009
Time:	TTh: 2:40-3:55	Place	1024 Mudd
Professor:	Kathy McKeown	Office Hours:	Tu 4-5,We 4-5, 722 CEPSR
Email:	kathy@cs.columbia.edu	Phone:	212-939-7114
Teaching Assistant:	Sara Rosenthal	Office Hours:	M 5:30-6:30, 726 CEPSR Th 1:30-2:30
	Kaushal Lahankar		Th 4-5, TA Room, Mudd 122A M 2-3
Email:	ss3067@columbia.edu	Phone:	212-939-7122

Announcements || Academic Integrity || Submission Directions || Description
Links to Resources || Requirements || Syllabus || Text

Announcements:

1. Check Columbia Courseworks for announcements, your grades (only you will see them), and discussion. Professor McKeown 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 McKeown know. The NLP group often has research opportunities available.

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, 2^nd Edition,Â 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.

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".

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 8	Introduction and Course Overview	Ch 1
	Sep 10	Natural Language and Formal Language: Regular Expressions and Finite State Automata	Ch 2, 3
2	Sep 15	N-grams and Language Models	Ch 4	HW1 assigned WSJ article
	Sep 17	POS Tagging	Ch 5
3	Sep 22	HMMs and POS	Ch 6
	Sep 24	Context-Free Grammars	Ch 12.1-12.14
4	Sep 29	Parsing with Context Free Grammars and Evaluation of POS taggers	Ch 13	HW 1 due
	Oct 1	Probabilistic and Lexicalized Parsing Presentation on using NLTK	Ch 14.1-14.7	HW2 assigned Where the Wild Things Are NLTK Readme POS guide Text for the Stanford parser
5	Oct 6	Representing Meaning	Ch 17-17.2, 17.4
	Oct 8	Semantic Analysis	Ch 18.1-18.4
6	Oct 13	Semantic Analysis	Ch 19
	Oct 15	Word Sense Disambiguation	Ch 20.1-20.5
7	Oct 20	Machine Learning Approaches to NLP and Introduction to Weka	Jansche&Abney02	HW 2 due at midnight (err.. 11:59PM) on 10/21
	Oct 22	Semantic Application and Midterm Review
	Oct 27	Midterm (midterm solutions)	Sample midterm
	Oct 29	Words Eye		Guest Speaker: Robert Coyne
8	Nov 3	Holiday	Holiday	Holiday
	Nov 5	Summarization, Weka slides	Ch 23.3-23.7	HW 3 assigned , HW3 FAQ
10	Nov 10	Summarization
	Nov 12	Organizational Details Information Extraction	Ch 22.1-22.4
	Nov 17	Information Retrieval and Question Answering	Ch 23.1-23.2
	Nov 19	Pronouns and Algorithms for Reference Resolution	Ch 21.3-21.5	HW 3 due, 11:58PM, Sunday Nov. 22^nd EXTENSION: HW3 due 11:58 Nov. 25th
	Nov 24	Text Coherence and Discourse Structure	Ch. 25	HW 4
	Dec 1	Generation	Papers
13	Dec 3	Machine Translation And Philipp Koehn’s tutorial	Ch 21.1-21.2
	Dec 8	Applications using discourse	Papers
14	Dec 10	The future and Final Review A practice final exam		HW 4 due, 11:58 pm, Dec. 13th

	Dec. 15-16			Study Days
	Dec. 17-23			Final Exams