HON 111.1 - Fall 2014 - Syllabus
Honors Topics Seminar - Computers playing Jeopardy!
Course Objectives and Description
Honors topics course: these courses, which use alternative learning modes, are intended to enrich the Honors College experience by introducing students to specific aspects of community, academic, and creative life at the University, on Long Island, and in the New York metropolitan region. Past topics have included: the lives of scientists; current events; Long Island ecology; contemporary art; musical performance at Stony Brook; the language of dance; immigration; cultural diversity; entrepreneurship. Each course culminates in the writing of a short, substantive paper. May be repeated as the topic changes.
This Computers playing Jeopardy! class is about the IBM Watson project.
IBM Watson is a computer system capable of answering rich natural language questions and estimating its confidence in those answers at a level of the best humans at the task. On Feb 14-16, 2011, in an televised event, Watson triumphed over the best human players of all time on the American quiz show, Jeopardy!. In this course we will discuss the main principles of natural language processing, computer representation of knowledge and discuss how Watson solved some of its answers (right and wrong).
Prerequisite: Acceptance into the Honors College
Instructor: Dr. Paul Fodor
1437 Computer Science Department, Stony Brook University
Office hours: Wednesdays&Fridays 9:00AM-10:30AM and By Appointment
Phone: (631) 632-9820
Email: pfodor (at) cs (dot) stonybrook (dot) edu
- Lectures: Mondays 9:00AM - 10:50AM, 7-week option, Computer Science Building 2116.
- Provide a conceptual understanding of how IBM Watson software system works.
- Introduce the students to important natural language processing techniques such as parsers, question analysis, and text search.
- Improve critical thinking by developing evaluative, problem-solving, and expressive skills.
- Enhance group communication skills through discussions, small-group work, presentations or debates.
- Develop intellectual curiosity and better understand the role of a student in an academic community.
The following learning outcomes are expected for students completing this course:
- Demonstrate knowledge and understanding of a conceptual understanding of how IBM Watson software system works.
- Demonstrate knowledge and understanding of important natural language processing techniques such as parsers, question analysis, and text search.
No required textbooks. We will use material from:
Jurafsky, D. and Martin, J. H. Speech and Language Processing. Prentice Hall. 2000. ISBN: 0130950696.
Manning, C. D. and Schütze, H. Foundations of Statistical Natural Language Processing. The MIT Press. 1999. ISBN 0262133601.
Students will be evaluated on the basis of homework and lab work, participation in discussion of lecture materials, and interaction with faculty and other students. Because of the variety of offerings, it is not possible to specify precise breakdowns of the value of each type for all sections. The grades are posted on Blackboard: http://blackboard.stonybrook.edu.
- Class Participation (20% of the final grade): Students are expected to contribute their own ideas and to ask questions during class.
- Class Attendance (20% of the final grade): Students are expected to attend all of the class sessions for the First-Year Seminar. More than 2 absences will result in an unsatisfactory grade.
- Assignments (60% of the final grade): there will be short homework survey and presentation, and class assignments.
- Required Reading: before each class there will be required reading relevant to that class.
Americans with Disabilities Act
If you have a physical, psychological, medical or learning disability that may impact your course work, please contact Disability Support Services, ECC (Educational Communications Center) Building, room128, (631) 632-6748. They will determine with you what accommodations, if any, are necessary and appropriate. All information and documentation is confidential.
Each student must pursue his or her academic goals honestly and be personally accountable for all submitted work. Representing another person's work as your own is always wrong. Faculty are required to report any suspected instances of academic dishonesty to the Academic Judiciary. Faculty in the Health Sciences Center (School of Health Technology & Management, Nursing, Social Welfare, Dental Medicine) and School of Medicine are required to follow their school-specific procedures. For more comprehensive information on academic integrity, including categories of academic dishonesty, please refer to the academic judiciary website at http://www.stonybrook.edu/uaa/academicjudiciary.
Critical Incident Management
Stony Brook University expects students to respect the rights, privileges, and property of other people. Faculty are required to report to the Office of Judicial Affairs any disruptive behavior that interrupts their ability to teach, compromises the safety of the learning environment, or inhibits students' ability to learn. Faculty in the HSC Schools and the School of Medicine are required to follow their school-specific procedures.