|CS574 Language Technologies|
|Time and Place|
|Mondays and Wednesdays, 2:55-4:10
course studies computational techniques for large-scale text-processing
applications including: information retrieval, text classification,
information extraction, document clustering, document ranking,
summarization, topic detection and tracking, and question answering. The
course focuses on statistical and machine learning approaches to these
natural language processing tasks as well as methods for their empirical
|Lecture Notes, Slides, and Handouts|
|Electronic versions of handouts, homeworks, and lecture slides
will be made available (when available). Hardcopies will be provided in class.
|We will provide reading material and hand it out in class.
For further reading, we recommended parts of the following books:
|Any of the following:
Roughly: A=90-100; B=80-90; C=70-80; D=60-70; F= below 60
Late assignment policy: Barring
extenuating circumstances, all homeworks and critiques must be
turned in on the date specified, AT THE START OF CLASS.
Assignments turned in within 24 hours of the due date will be
penalized one full grade (e.g. A-->B). Assignments
more than 24 hours late will not be accepted.
| 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.
Professor Cardie received NSF support under Award 0074896 for development of this course. Any opinions, findings, and conclusions or recommendations expressed in these materials or on this web site are those of the instructors and do not necessarily reflect the views of the National Science Foundation.