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Course Description
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Policies & Grading

Introduction to Natural Language Processing

CMPSCI 585
Fall 2004

Policies

Prerequisites: CMPSCI 287. (CMPSCI 383 is encouraged but not required.)
Credits: 3 units.

Grading:

30% three programming assignments
10% five short written homeworks
20% final project
15% midterm exam
15% final exam
10% classroom participation & possible quizzes

Homework submission: Homework is due as indicated on the homework assignment, on paper, at the beginning of class. Homework must be type-written, not hand-written.  Late homework submissions will be accepted at the discretion of the instructor, but in no case after a solution set has been handed out, and there will be grading penalties for late assignments.

Rescheduling exams: Exams may be taken other than at the scheduled time, but only under exceptional circumstances and then only if approved by the instructor well before the exam. It is your responsibility to contact the instructor and justify your cause.  Makeup exams will rarely be the same as the original exam, and will usually be all or partly oral.

Academic Honesty: Your work must be your own. You are encouraged to discuss problems with other students, but the answer, the programming, the writing, and the final result that you hand in must be your own effort. Discussing or sharing answers to specific problems is considered dishonest. If you have questions about what is honest, please ask! You are strongly encouraged to cite your sources if you received extraordinary help from any person or text (including the Web). Computer Science Department policy specifies that the penalty for cheating is (1) a final course grade of "F" and (2) possible referral to the Academic Dishonesty Committee. The UMass policy can be found here.

Software and Data: You may be using copyright-protected software and/or data in the laboratory. Federal law and license agreements between the University and various software producers and data-providers prohibit extra-curricular copying for any purpose. Such activity will be regarded as a form of cheating and will be dealt with as such.

Incompletes: An incomplete will be given only when documented, exceptional circumstances beyond your control have made it impossible to complete the assigned work before the end of the semester. It is your responsibility to contact the instructor regarding any such problems well before the end of the semester. Note that general rules of the University allow an incomplete only if most of the work has been completed satisfactorily before the end of the semester, so that the incomplete can be finished within the first four weeks of the immediately following semester. They further state that if a substantial amount of work remains undone then a retroactive drop should be obtained and the entire course repeated.

Auditing: Official auditors will normally be expected to complete all of the homeworks and programming assignments, and to achieve at least a C-level performance . Anyone enrolled for audit should contact the instructor early in the semester to discuss the requirements for receiving audit credit for this course.  If the course is heavily over-enrolled, audits may not be possible.

Attendance: Students are expected to attend each class. Attendance will not be taken directly, but absence may be noted because of occasional in-class assignment. The official means of communication for this course will be in-class announcements, though every effort will be made to ensure that important announcements go out on the course mailing list or appear on the course Web pages.

Office hours: The instructor will normally be available in his offices during posted office hours. Outside of those hours, or times arranged on an appointment basis, he cannot be assumed to be available for course-related matters, even if in his offices.

Course Web page: The class World Wide Web page is http://www.cs.umass.edu/~mccallum/courses/inlp2004. Assignments, online materials, and notes about assignments will be available from this page.


Required book : Manning and Schutze, "Statistical Natural Language Processing"
Additional optional sources: Jurafsky and Martin