University of Southern California

CSCI 544 — Applied Natural Language Processing

Spring 2019

Latest Announcements


Time and location Monday 4:00pm–7:50pm, THH 201
Instructor Ron Artstein Monday 2:00pm–3:30pm, RTH 512, or by appointment
Teaching Assistants Sami Abu-El-Haija Wednesday 4:00pm–6:00pm, SAL computer lab
Umang Gupta Monday 10:00am–11:59am, RTH 3rd floor lobby
Ramesh Manuvinakurike Wednesday 10:15am–12:15pm, SAL computer lab

There will be no office hours on January 21 (Martin Luther King’s Birthday), February 18 (Presidents’ Day), or March 10–17 (Spring Recess).


Administrative Matters

Registration and D-Clearance
Please consult the page on D-clearance and waiting list
Graders
If you’ve taken the course before and wish to be considered as a grader, please apply through the Computer Science Department. Graders are usually selected in the first few weeks of the semester.
Travel
Students who are absent from class for any reason must make up the materials themselves, and must submit their assignments on time. The final exam will be administered on-line, according to the Final Exam Schedule. University regulations do not allow a student to omit a final examination, or take it in advance of its scheduled time.
Academic integrity
Please read my note on academic integrity.

Synopsis

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 graduate course is intended for:

Recommended preparation: Proficiency in programming, algorithms and data structures, basic knowledge of linear algebra and machine learning.

Related Courses

This course is part of USC’s curriculum in natural language processing. There is a sister course, CSCI 662 Advanced Natural Language Processing, offered in the Fall semester, which covers complementary (and advanced) material and is intended for PhD students (or students who want to continue to a PhD program).

Course Objectives

Students in the course will learn to perform the following:

  1. Read technical literature in Natural Language Processing (including original research articles) and answer questions about such readings.
  2. Implement language processing algorithms and test them on natural language data.
  3. Solve language processing problems and explain the reasoning behind their solutions.

Coursework and Grading

This course will not have a research project.

Grading scale

The following scale is used for determining final grades (note that A is the highest grade given by USC).

Grade challenges

Late Policy

Communication

Please use the class discussion boards on Piazza for questions and issues regarding homework assignments and the course in general. This way, the entire class can participate and see the questions and answers. Email should be reserved for communication of a personal nature. If we receive questions by email where the response could be helpful for the class, we may ask you to repost the question on the discussion boards.

Any special requests must be submitted in writing (I am not able to correctly remember individual conversations with 200 students).

Notes and presentation materials

I usually teach using the blackboard, not with prepared slides. My written lecture plans are fairly skeletal and not very useful to students. I therefore, as a general rule, do not distribute notes or presentation materials to the class. Students are expected to attend the lectures, participate in the discussions, and take notes. Students are welcome to organize for note-taking, and are encouraged to distribute and share notes among students in the class. Audio and video recording of lectures for personal use is generally allowed, provided that it is done in a non-disruptive way. Any distribution, posting or publication of notes or recordings from my lectures outside this class (for example, on a public web site) requires my prior approval.

Resources

Recommended textbooks

The course does not have a textbook. Required readings will be specified in the schedule below as the course progresses, and will include a combination of select textbook chapters as well as original research articles. The links below give access to the full text of several textbooks; these are useful for general background on Natural Language Processing, and to supplement some of the materials taught in class. Any chapters that are required will be detailed in the schedule; otherwise, these texts are not required.

Schedule

Note: The weeks of January 21 and February 18 are instructional weeks. Class will not be held on these days because they are university holidays, but work will be assigned for the week and is due at the appropriate time.

Topics listed in the schedule are tentative and subject to change.

Statement on Academic Conduct and Support Systems

Academic Conduct:

Plagiarism – presenting someone else’s ideas as your own, either verbatim or recast in your own words – is a serious academic offense with serious consequences. Please familiarize yourself with the discussion of plagiarism in SCampus in Part B, Section 11, “Behavior Violating University Standards” https://policy.usc.edu/scampus-part-b/. Other forms of academic dishonesty are equally unacceptable. See additional information in SCampus and university policies on scientific misconduct, http://policy.usc.edu/scientific-misconduct.

Support Systems:

Student Health Counseling Services – (213) 740-7711 – 24/7 on call
engemannshc.usc.edu/counseling
Free and confidential mental health treatment for students, including short-term psychotherapy, group counseling, stress fitness workshops, and crisis intervention.

National Suicide Prevention Lifeline – 1 (800) 273-8255 – 24/7 on call
http://www.suicidepreventionlifeline.org
Free and confidential emotional support to people in suicidal crisis or emotional distress 24 hours a day, 7 days a week.

Relationship and Sexual Violence Prevention Services (RSVP) – (213) 740-4900 – 24/7 on call
https://engemannshc.usc.edu/rsvp/
Free and confidential therapy services, workshops, and training for situations related to gender-based harm.

Office of Equity and Diversity (OED)/Title IX – (213) 740-5086
https://equity.usc.edu/,  http://titleix.usc.edu/
Information about how to get help or help a survivor of harassment or discrimination, rights of protected classes, reporting options, and additional resources for students, faculty, staff, visitors, and applicants. The university prohibits discrimination or harassment based on the following protected characteristics: race, color, national origin, ancestry, religion, sex, gender, gender identity, gender expression, sexual orientation, age, physical disability, medical condition, mental disability, marital status, pregnancy, veteran status, genetic information, and any other characteristic which may be specified in applicable laws and governmental regulations.

Bias Assessment Response and Support – (213) 740-2421
https://studentaffairs.usc.edu/bias-assessment-response-support/
Avenue to report incidents of bias, hate crimes, and microaggressions for appropriate investigation and response.

The Office of Disability Services and Programs – (213) 740-0776
http://dsp.usc.edu
Support and accommodations for students with disabilities. Services include assistance in providing readers/notetakers/interpreters, special accommodations for test taking needs, assistance with architectural barriers, assistive technology, and support for individual needs.

USC Support and Advocacy – (213) 821-4710
https://studentaffairs.usc.edu/ssa/
Assists students and families in resolving complex personal, financial, and academic issues adversely affecting their success as a student.

Diversity at USC – (213) 740-2101
https://diversity.usc.edu/
Information on events, programs and training, the Provost’s Diversity and Inclusion Council, Diversity Liaisons for each academic school, chronology, participation, and various resources for students.

USC Emergency – UPC: (213) 740-4321, HSC: (323) 442-1000 – 24/7 on call
http://dps.usc.edu/,  http://emergency.usc.edu
Emergency assistance and avenue to report a crime. Latest updates regarding safety, including ways in which instruction will be continued if an officially declared emergency makes travel to campus infeasible.

USC Department of Public Safety – UPC: (213) 740-6000, HSC: (323) 442-1200 – 24/7 on call
http://dps.usc.edu
Non-emergency assistance or information.

USC Viterbi Honor Code

The Code was developed by Viterbi students, and its text is as follows:

Engineering enables and empowers our ambitions and is integral to our identities. In the Viterbi community, accountability is reflected in all our endeavors.

These are the pillars we stand upon as we address the challenges of society and enrich lives.

Academic Integrity Violations

All coding and writing must be done individually (unless instructed otherwise), and not copied from other students. Copying or plagiarism is grounds for failure of an assignment, or in serious cases failure of the course.

Use of the internet or other outside resources to find solutions to homework problems is considered cheating.

Please read my note on academic integrity.