This course is designed to introduce students to the fundamental concepts and ideas in natural language processing (NLP), and to get them up to speed with current research in the area. It develops an in-depth understanding of both the algorithms available for the processing of linguistic information and the underlying computational properties of natural languages. Word-level, syntactic, and semantic processing from both a linguistic and an algorithmic perspective are considered. The focus is on modern quantitative techniques in NLP: using large corpora, statistical models for acquisition, disambiguation, and parsing. Also, it examines and constructs representative systems.
Graduate students and advanced undergraduates specializing in computer science, linguistics, or symbolic systems.
Textbook and Readings
The required text is:
It's at the bookstore (and other purveyors of fine books). Of course, I'm also fond of:
Other useful reference texts for NLP are:
Other papers with relevant material will occasionally be posted or distributed for appropriate class lectures.
Copies of in-class hand-outs, such as readings and programming assignments, will be posted on the syllabus, and hard copies will also be available outside Gates 158 (in front of Prof. Manning's office) while supplies last.
Assignments and Grading
There will be three substantial programming assignments, each exploring a core NLP task. They are a chance to see real, close to state-of-the-art tools and techniques in action, and where students learn a lot of the material of the class.
There will be a final programming project on a topic of your own choosing.
Finally, there will be simple in-class quizzes based on the day's lecture, which will aim to check that you are paying attention to what you hear/read.
Course grades will be based 60% on programming assignments (20% each), 6% on the quizzes, and 34% on the final project.
Be sure to read the policies on late days and collaboration.
Sections will be held most weeks to go over background material, or to address issues related to the programming assignments. Sections are optional, but students are encouraged to attend for a better understanding of background material and the assignments.
Facebook: CS224N Group
Staff mailing list:
Announcements mailing list:
Enrolled students are automatically subscribed.
Assignment 1 (due 4/15/09)
The Stanford NLP Group
Site design by Bill MacCartney