Course Title: Self-Paced Lab for Information Retrieval (11-742)
Department: Language Technologies Institute (LTI)
Units: 6
Semester: Both
Instructor: Yiming Yang
Corequisite: Information Retrieval (11-741)

Course Outline:

The Self-Paced Lab for Information Retrieval (IR Lab) is intended to complement the 11-741 lecture course (IR Core) by providing a chance for hands-on, in-depth exploration of various IR research topics. Students will design their own projects (project examples) and discuss instructor for approval. Each student will work independently. If multiple students work as a team on a particular topic, each should choose an approach that is different from the approaches used by the other students working on the same problem. Make a Web page for progress report and communication. Your Web page will be checked by the instructor periodically thus should be updated timely to reflect your on-going progress and work organization. The Web pages will also serve a role of data/tools sharing among students.

Requirements & Milestones:

·          Literature survey and work planning. Each student must pick a project and write a literature survey by the end of the second week. You should read at least two key papers in related areas as recommended or of your own choices. The survey should make a connection to the planned work, including a statement of the objectives, the description of your approach, the design of your experiments, and the estimated significance of your contribution.

·          A time table of planned steps is also required. All the information should be made available on the Web page (with a notification to the instructor).

·          Implementation of proposed method(s), algorithm(s) or comparison among methods. The lab requires exercising and demonstrating programming skills in IR, in conjunction with analytic skills.

·          Preliminary results. By the seventh week, preliminary results are expected. A two-page progress summary is required, which should include an informative and concise description of your algorithm(s), an analysis of your preliminary results, and an outline of the remaining work. Details of the experiments can be provided via the Web page.

·          Documentation and presentation
a) write and submit a final report on your system and experiments;
b) submit the final version of your documented codes with usage description (for the re-use of your codes by others);
c) present your work to the instructor (and possibly other students); arrange your time with the instructor through email.

Grading Criteria:

• How meaningful the topic and the approach are, how carefully the study is carried out, and how significant the findings are compare to those reported by other students or in the literature.
• The quality and quantity of the programming part, and appropriateness of  documentation.
• How well the approach/results are present in written and oral forms.