CS772: Advanced Natural Language Processing Concepts
Spring 2010


Information
Syllabus
Suggested Readings

Summary

This is a seminar-style course devoted to recent research in statistical techniques for the automatic analysis of natural (human) language data. The instructor will give some lectures on the fundamentals and ask students to present topical papers. The topics covered in this course are: syntactic language models and large-scale distributed language models, search algorithms, statistical machine translation and non-parametric Bayesian models/processes (Dirichlet, Pitman-Yor, Indian-Buffet, etc) for natural language processing.

Lectures

Time: Monday/Wednesday 8:00 pm - 9:15 pm; Location: Medical Sciences 220

Instructor

Shaojun Wang
387, Joshi Center
shaojun.wang(at)wright.edu
(937) 775-5140
Office hours: Tuesday/Thursday 2:30PM-4:00PM

Textbooks

Philipp Koehn.
Statistical Machine Translation
Cambridge University Press, 2010.

D. Jurafksy and J. Martin.
Speech and Language Processing, 2nd Edtion
Prentice Hall, 2008.

J. Pitman.
Combinatorial Stochastic Processes
Springer, 2006

Course Grades and Workload

Paper Presentations. These should be done individually. You will read one or more papers and give a 45 minutes class presentation. When someone else give his/her presentation, you need to do three things: read the papers he's presenting, write reviews about the papers, finally give a grade on the presentation.