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OverviewThis course is concerned with concepts, models and algorithms to interpret, generate and learn natural languages, as well as applications of NLP. It deals with a wide range of issues such as parsing, semantic interpretation, discourse/text processing, knowledge representation and the acquisition of grammatical and lexical knowledge. The goal of the course is for the students to be familiar with basic concepts in NLP, understand the algorithms and methods for NLP and acquire the skills for developing NLP tools/systems. Grading
Plagiarism and CheatingMake sure you have
read and are familiar with the Code of Student Behaviour in the Except as described on certain assignments, all work is to be done individually. If work is handed in where, in the opinion of the lab instructor and/or one of the lecture instructors, it is too similar to have been done individually, a grade of 0 will be assigned for that work to all parties in the course that are involved. In such a situation, the individuals who are involved will be notified of this action by email sent to their Unix account. At that time, the individuals should contact the lecture instructor to discuss the matter, especially if they feel the action is unwarranted; contact must be within 48 hours of the sending of any such messages. Failure by the student to reply within 48 hours after sending of the message will be taken as a refusal on their part to discuss the matter further. Comparison of work will not be limited only to work handed in during this term. If it is discovered that work handed in is excessively similar (using the above criteria) to work handed in during a past term, not only will the above procedure and penalties apply, but the students in this course that are involved in this will be reported to their Dean. The Dean will decide on a further action (can result in being assigned a grade of 1F for the course and an extended suspension from university). |
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Copyright © 2004 Dekang Lin
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