| Fall 2012 |
| Time: Tuesdays and Thursdays, 1:25-2:40 Place: 202 Thurston Instructors: Professor Claire Cardie, 5161 Upson Hall; Professor Lillian Lee, 4152 Upson Hall Office hours: see top of Claire's home page/"contact info" section of Lillian's home page |
| Course Management System (CMS): We'll be using the CS department course management system for submission of assignments, grading, etc. You can get to CMS via the above link. You'll need your Cornell netid and password. electronic submission instructions (specifically, page 5). Lectures and Assignments Resources: List of general NLP resources (from a prior run of this course) NLP resources available locally are listed under the local resources link of the Cornell NLP home page. |
| Course Description |
| Graduate-level introduction to technologies for the computational treatment of information in human-language form, covering natural-language processing (NLP) and/or information retrieval (IR). |
| Possible Topics to be Covered |
| Information extraction Information retrieval models Text categorization Topic modeling Question answering systems Summarization Machine translation Dialogue systems Language modeling Word-sense disambiguation Part-of-speech tagging Parsing Semantic analysis Discourse processing Coreference analysis NL generation |
| Reference Material |
| The optional text book for the course is: Daniel Jurafsky and James H. Martin, Speech and Language Processing, Prentice-Hall, 2008 (2nd edition) Other useful references: Christopher Manning and Hinrich Schutze. Foundations of Statistical NLP, MIT Press, 1999. Robert Dale, Hermann Moisl and Harold Somers, eds. Handbook of Natural Language Processing, 2000. Frederick Jelinek. Statistical Methods for Speech Recognition, MIT Press, 1998. |
| Grading |
40%: semester project problem description and summary of related work (5%), short presentation in class on the planned project (5%), progress report 1 (2.5%), progress report 2 (2.5%), in-class presentation (10%), final report (15%). 10%: participation You'll be expected to participate in class discussion or otherwise demonstrate an interest in the material studied in the course. 20%: one-page critiques of further-direction/project proposals based on research-paper readings (sample) 29%: research paper presentations1%: course evaluations |
| Academic Integrity |
| You are responsible for knowing and following Cornell's academic integrity policy. Absolute integrity is expected of every Cornell student in all academic undertakings; he/she must in no way misrepresent his/her work fraudulently or unfairly advance his/her academic status, or be a party to another student's failure to maintain academic integrity. The maintenance of an atmosphere of academic honor and the fulfillment of the provisions of this Code are the responsibilities of the students and faculty of Cornell University. Therefore, all students and faculty members shall refrain from any action that would violate the basic principles of this Code. Violation of the academic integrity policy will not be tolerated, and will result in an F in the course. See the University Code of Academic Integrity. |