CSCI 544 Applied Natural Language Processing

Fall 2015

Instructors

Our on-campus office hours are either in PHE 514 or PHE 516. In addition to the listed office hour, office hours are also by appointment.

• Mark Core: core [AT] ict.usc.edu (office hour: Wed 2:30-3:30)
• Kallirroi Georgila: kgeorgila [AT] ict.usc.edu (office hour: Mon 2:30-3:30)

TAs

Currently, you should go to the SAL computer lab to find the TAs during their office hours.

• Chris Wienberg: cwienber [AT] usc.edu (office hours: Mon 2-4)
• Ali Jalal-Kamali: jalalkam [AT] usc.edu (office hours: Wed 2-4)

Lectures

• Calendar with holidays and past and future lecture topics
• Section 30089D meets Mon/Wed 4-5:50PM at WPH B28.
• Section 30090D meets Mon/Wed 6-7:50PM at GFS 106.

Resources

• Piazza: discussion (first place to go to ask questions) and announcements.
• Blackboard: lecture slides.

Course summary:

This course covers both fundamental and cutting-edge topics in Natural Language Processing (NLP) and provides students with hands-on experience in NLP applications. This is part of USC's curriculum in computational linguistics. The course will roughly follow the previous semester's course taught by Kenji Sagae. There will be some differences in topics covered and assignments/projects. Like the previous course, there will be no exams. The grade for the class will be based only on assignments and a project. There will be no final exam and the class will finish December 4th at midnight (i.e., the last project/assignment will be due at that time or earlier).

Grading:

• Programming assignments (4 x 15%): the grades will depend on the performance of a system and a technical report.
• Research project (40%): this will be a group project, graded individually: 30% of the grade will depend on the project's relevance to the course, degree of difficulty, amount of work, correctness and written report. 10% of the grade will depend on a written report about projects from other groups.

Software for the course

To complete the assignments you will need the following tools.

• Specific Ubuntu Linux setup. This is the same environment we will use for grading.
• Python 3
• All the documentation
• Documentation on reading command line arguments
• Tutorial with tips for working with files
• Bitbucket
• Git

Assignments and project

• Assignment 1: Due Sept. 7
• Assignment 2: Due Sept. 30
• Assignment 3: Due Oct. 28
• Assignment 4: Due Nov. 23 (this assignment is on Blackboard under Content)
• Proposal for Group Project: Due Nov. 19
• Guidelines regarding group presentations: slides due Nov. 29
• Final Project: Due Dec. 6

CSCI 590 section 30181 (Directed Research)

The course registration page states you must also enroll in CSCI 590 section 30181. This is to ensure you receive 4 units for the course. Although 590 is Directed Research, you will receive credit automatically for it, if you earn a passing grade for the course. You should receive more information directly from the department about the process.