Course Info for Ling645/CMSC723, Fall 2005

Course Info for Ling645/CMSC723, Fall 2005
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

Instructors:
Philip Resnik and David Chiang.
TA:
Jae-Yong Lee
Location and time of the class:
Computer Science Instructional Center (CSIC) Room 3120, Wednesdays, 4-6:30pm.
Text:
Weekly readings listed in the schedule of topics, mostly from Dan Jurafsky and James Martin, "Speech and Language Processing: An Introduction to Natural Language Processing, Speech Recognition, and Computational Linguistics", Prentice-Hall (2000). (Make sure to check the errata for the textbook as you do your readings. Also see the updated chapters page for recent updates. )
Syllabus:
See the schedule of topics.
Office hours:
David Chiang: Mondays 2-3pm, AVW 3161.
Jae-Yong Lee: Fridays 4-5pm, AVW 1112 (in front of Heather's old office).
Philip Resnik: By appointment.

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 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. CS MS comp grade (AI area) will be based entirely on the average of the two exams.
Class assignments/projects (40%): 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.
Class participation (10%): 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 us 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 are:

  /afs/glue.umd.edu/class/fall2005/ling/645/0101
  /afs/glue.umd.edu/class/fall2005/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.