Term: Winter 2006
Course No.: 767
Credit Hours: 3
Instructor: D. Radev
Prerequisites: EECS 595 or EECS 597 or SI 650 or permission of instructor
Course Description:
The course will focus on reading recent research papers on topics in
NLP and IR such as statistical machine translation, expectation
maximization, text classification, sentiment and polarity analysis,
information extraction using conditional random fields, document
models for IR, semi-supervised learning, latent semantic analysis,
spectral methods, noisy channel models, graph-based ranking methods,
label propagation algorithms, etc.
The course is appropriate for students who have already taken either
of the following classes: "Natural Language Processing", "Information
Retrieval", "Language and Information", and/or "Machine Learning". I
can also grant exemptions to other motivated students who can convince
me that they can follow the course material.
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