This course is a graduate level introduction to natural language processing, the primary concern of which is the study of human language from a computational perspective.
The class will cover models at the level of syntactic, semantic and discourse processing. The emphasis will be on corpus-based methods and algorithms, such as Hidden Markov Models and probabilistic context free grammars. We will discuss the use of these methods and models in a variety of applications including syntactic parsing, information extraction, statistical machine translation, and summarization.
This subject qualifies as an Artificial Intelligence and Applications concentration subject.
Technical Requirements
File decompression software, such as Winzip® or StuffIt®, is required to open the .gz and .tar files found on this course site. Postscript viewer software, such as Ghostscript/Ghostview, can be used to view the .ps files found on this course site.