Natural Language Processing

In this course we will introduce statistical techniques for inferring structure from text. The aim of the course is to introduce existing techniques in statistical NLP and to stimulate thought into bettering these. We will look in detail at the application of NLP in Information Retrieval, Information Extraction, Dialog based Transaction Systems and Machine Translation.

Prerequisites:

• Programming skills (any favourite language will do).
• Basic maturity in mathematics.
• We will build on all key concepts in class.

• Foundations of Statistical Natural Language Processing, Chris Manning and Hinrich Schütze, MIT Press. Cambridge, MA: May 1999.

• J. F. Allen, Natural Language Understanding, Benjamin Cummings, 1987, Second Edition, 1994.
• Other Texts and Papers prescribed from time to time.
• Other Resources.

• Minor I & II: 30
• Major: 20
• Homework: 30
• Project: 20

• Class Location: CSE Seminar Room.
• Class Timings: Tu and Th 5.00 PM - 6.30 PM.

Assignments will typically be handed out in the first class of the week and will be due in the first class of the following week. Solutions will be posted within two weeks. In parallel longer duration projects will also be handed out. Late assignments will not be graded. Innovative and good ideas presented in solutions to assignments will be rewarded with bonus marks. The homework is to be done individually. If any help is needed please consult only the instructor.

• Jan. 02, 2002............Course Information [ppt]
• Jan. 02, 2002............Introduction [ppt]
• Jan. 04, 2002............Mathematical Foundations [ppt] slides by Barbara Rosario (UC Berkeley) [reproduced with author's permission].
• Jan. 10, 2002............Linguistic Essentials [ppt]
• Jan. 10, 2002............Statistics and Linguistics [ppt]
• Jan. 10, 2002............Corpus-Based Work [ppt]
• Jan. 15, 2002............Collocations [ppt]
• Jan. 17, 2002............Statistical Inference: n-grams [ppt]
• Jan. 22, 2002............n-grams in Speech Recognition [ppt] and in Machine Translation [ppt]
• Jan. 24, 2002............Wordsense Disambiguation [ppt]
• Jan. 31, 2002............Web Search Engines [ppt]
• Feb. 07, 2002............Lexical Acquisition [pdf] slides by Manning and Schütze [link to their site].
• Feb. 15, 2002............Latent Semantic Analysis [ppt] Guest Lecture by Dharmendra P. Kanejiya (IIT Delhi).
• Feb. 21, 2002............Applications of Latent Semantic Analysis [ppt] Guest Lecture by Dharmendra P. Kanejiya (IIT Delhi).
• Feb. 26, 2002............Hidden Markov Models [ppt] slides by David Blei (UC Berkeley) [reproduced with author's permission].
• Feb. 28, 2002............Parts-of-Speech Tagging [ppt]
• Mar. 05, 2002...........Probabilistic Context Free Grammars [pdf] [ps] slides by Manning and Schütze [link to their site].
• Mar. 21, 2002...........Probabilistic Parsing [ppt]
• Apr. 02, 2002...........Spoken Dialogue Systems [ppt]
• Apr. 04, 2002...........Clustering [ppt]
• Apr. 09, 2002...........Topics in Information Retrieval [ppt]
• Apr. 11, 2002...........Introduction to Statistical Machine Translation [ps] slides by Raghavendra Udupa (IBM, India Research Lab).

• Class discussion topics.

• Week by week readings.

Downloadable Assignments, Minors, Major and Project:

• Assignment 1 due Jan. 10, 2002.
• Assignment 2 due Jan. 17, 2002.
• Assignment 3 due Jan. 24, 2002.
• Assignment 4 due Feb. 12, 2002.
• Assignment 5 due Feb. 19, 2002.
• Assignment 6 due Mar. 05, 2002.
• Assignment 7 due Mar. 12, 2002.
• Minor 1 Feb. 12, 2002.
• Minor 2 Mar. 19, 2002.
• Major Apr. 18, 2002.
• Project due Apr. 16, 2002.

• Course Statistics.