Course Info for Ling723/CMSC723, Fall 2006
Course Info for Ling723/CMSC723, Fall 2006
Computational Linguistics I
Class mailing list
Once we've gotten it set up, students should be on the class
mailing list. Messages are archived on a weekly basis.
Essentials
What's the course about?
This is the first semester in our two-semester graduate sequence in
computational linguistics. In the first semester, we will be
disussing fundamental methods in natural language processing, with a
focus on core representations and algorithms. Topics include:
finite-state methods, context-free and extended context-free models of
syntax; parsing and semantic interpretation; n-gram and Hidden Markov
models, part-of-speech tagging; natural language applications such as
machine translation, automatic summarization, and question answering.
Students completing this course will have a solid working knowledge of
the basics of NLP and will be well prepared for the second semester
course, which covers natural language processing with a focus on
corpus-based statistical techniques.
Students taking this course should be competent programmers, since
concepts taught in class will sometimes be reinforced in practice by
hands-on programming assignments. We are not assuming a great deal of
familiarity with linguistics; students needing to get up to speed on
linguistics concepts will do fine with Jurafsky and Martin's material
on word classes and context-free grammars for English (in Chapters 8
and 9).
Please feel free to contact us with any questions, and feel free to
suggest the course to anyone who might be interested.
See the schedule of topics for
class-by-class plans.
How will the course be graded?:
Students will be evaluated on their ability to master the
content of the material in the course and to think
critically about ideas presented to them.
- Exams (50%): There will be a midterm exam and a
final exam. These will be take-home exams.
CS MS comp grade (AI area) will be based entirely on the average of the two exams.
- Class assignments/projects (45%):
There will be periodic homework assignments that may involve
on-paper exercises (e.g. walking through algorithms or
calculations), hands-on programming, or analysis of data.
There may be a substantial multi-week project, in place
of several smaller assignments, during the second half of
the semester.
- Class participation (5%):
Showing up for class, demonstrating preparedness, and contributing
to class discussions.
Policy for Incomplete Work
- Late assignments. If an assignment is late by
up to 24 hours, the grade will be reduced by 10%. By 48 hours, 20%.
And so forth. Exceptions can be discussed in cases of medical
excuses, family emergencies, equipment failure, etc., but being busy
is not a valid excuse, and the sooner you talk to us about a
problem the better.
There are several common problems that we are
unlikely to consider as valid reasons for failing to get
work in on time. These include (a) failure to manage your time
properly, (b) discovering an assignment is harder than you expected
it to be (see item a), and (c) losing code or data that should have
been backed up, unless it's someone else's fault.
- Late assignment exception. Each student can
ask to extend an assignment due date by 48 hours one time during
the semester, no questions asked.
- 'Incomplete' as a grade. We will not issue an
'incomplete' as a grade except for serious, valid reasons, generally
in the category of emergencies. See above for some reasons
unlikely to be considered valid. If you are having problems of any kind,
please talk to one of us as soon as possible.
Course Accounts
Class work will take place on Linux servers on the
OIT Computing Cluster -- log
in to linux.grace.umd.edu.
Students who do not already have a GLUE account should
request one so that
I can give you a course account.
The two class directories will be:
/afs/glue.umd.edu/class/fall2006/ling/723/0101
/afs/glue.umd.edu/class/fall2006/cmsc/723/0101
and student directories are available under subdirectory 'student'.
See the file
system page for the directory layout. and see the file
removal timeline for important information about what gets deleted
when at the end of the semester.
See instructions on
turning in programming assignments for important information.
Check out these notes for some
useful information about computing in the GRACE cluster environment
in C++, Python, and Java.