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 (see http://appliednlp.bitbucket.org). 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.