![STANFORD](images/stanford.seal64.gif) |
CS 224N -- Ling 237
Natural Language Processing
Spring 2004
|
In Spring 2005, CS 224N is MW 11:00-12:15 in Gates
B12. More info to come, but it'll still be something like the below description....
Lecture: MW 1:15-2:30 in
Mitchell Earth Sciences B67
Section: There is no longer any section this quarter.
Professor:
Christopher Manning
TAs:
Praveen Kankanala and
Jeanette Pettibone
Syllabus
FAQs
Announcements
[May 19, 2004] WSD results
are up! The testing data is now in the /wsdp/data/wsd_test directory.
[May 18, 2004] LATE DAY POLICY FOR THE FINAL PROJECT:
The wording in the late day policy might be a little confusing. It is
supposed to mean that there will be an nk total late day charge per group
(where n is the number of late days and k is the number of people in the
group). Usually n late days are assessed to each
team member, but the nk late days can be divvied up whatever way the
group choses (i.e., if a group of 3 turns it in 2 days late the group is
charged 6 late days of which 2 can be charged to each member or all 6
can be charged to one member, etc.).
[May 18, 2004] There will be no more sections for the rest of the
quarter. Use the extra time for your final project!
[May 18, 2004] Homework #7 has been modified. You will only be graded on
problems 2, 3, and 4. Do not do problem 1.
[May 11, 2004] Hey - there is now an online version of the Final Project Guidelines.
[May 6, 2004] Just to clarify, the written homework assignments must be
done individually (there are only 2 programming projects - the parser and
the word sense disambiguator - which are not to be done individually).
What this means is that you can discuss the problem in groups but that
each person must work through the assignment themselves and do their own
write-up. Working in groups is definitely a good thing. Just be sure to
follow the instructions on homework collaboration found in the
Course
Information handout.
[May 6, 2004] In general, the solutions for the homeworks can be found as
links from the syllabus.
[April 26, 2004] The textbook is now in the bookstore!
[Apr 19, 2004] FINAL PROJECTS
-
You are only allowed to use 2 late days for the final
project. It must be turned in by the Friday of that week (June 4,
2004).
-
Note that there is a special opportunity to work on a piece
of a joint project between Andrew Ng and Chris for your final project
(check out the Final Programming Project Guidelines handout - part 4,
number 1). If you're interested in this, it's best to get started asap.
-
You are encouraged to work on any project that is related to NLP, not just
one of the projects listed in the guidelines.
[Apr 7, 2004] All handouts that can be accessed electronically have a link
in the online syllabus. The
handouts that are not available electronically can be found outside Chris
Manning's office (Gates 418)
Old Announcements
Useful Information and Handouts
Course Description
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.
Prerequisites
-
Adequate experience with programming and formal structures (e.g., CS106
and CS103X).
-
Programming projects will be written in Java, so knowledge of Java (or a willingness
to learn on your own) is required.
-
Knowledge of standard concepts in artificial intelligence and/or computational
linguistics (e.g., CS121/221 or Ling 138/238).
-
Basic familiarity with logic, vector spaces, and probability.
Intended Audience
Graduate students and advanced undergraduates specializing in computer
science, linguistics, or symbolic systems.
Section
Sections will be held most weeks to go over background material, or to
work through problems of the sort found in written and programming assignments.
Students are strongly encouraged to attend sections for a better understanding
of background material and the assignments.
Textbook and Readings
The required text is
-
Christopher Manning and Hinrich Schütze,
Foundations
of Statistical Natural Language Processing. MIT Press, 1999. ($75
in the bookstore.)
Read the text
online!
Please see http://nlp.stanford.edu/fsnlp/
for supplementary information about the text, including errata, and pointers
to online resources.
Additional useful reference texts for NLP are:
- James Allen. 1995. Natural Language
Understanding. Benjamin/Cummings, 2ed.
- Gerald Gazdar and Chris Mellish. 1989. Natural Language
Processing in X. Addison-Wesley.
-
Dan Jurafsky and James Martin. 2000. Speech and Language Processing.
Prentice Hall.
Additional papers will occaisionally be distributed and discussed during
the course of the class.
Copies of in-class hand-outs, such as homework assignments and problem
set solutions, will be posted on the syllabus, and
hard
copies will also be available outside Gates 419 (in front of Prof Manning's room) while
supplies last.
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