CS598CXZ Advanced Topics in Information Retrieval (Fall 2016)

Instructor: ChengXiang Zhai

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Basic Information

Administrative

Readings

The required readings for this course are a combination of research papers, survey articles, and book chapters. Most of the readings should be available online (if not, hard copies will be made for you).

Prerequisites

Students are expected to have a good knowledge of basic probability and statisticcs in addition to programming skills at the level of CS225 or a similar programming course. Some background in one or more of the following areas: information retrieval, machine learning, natural language processing, data mining, or databases would be a plus, but not required. If you are not sure whether you have the right background, please contact the instructor.

Format

The course consists of a mixture of lectures by instructor and presentations by students. There will be frequent short written assignments and some exploratory assignments. There will be a 75-minute midterm exam to be given at the class in the middle or slightly after the middle of the semester. Each student is also required to finish a course project to do an in-depth study of a topic, aiming at producing a publication/submission or developing a novel useful system. Group work is allowed and encouraged.

Course Policy and Grading

  1. Attendance
  2. Attendance is mandatory, but use common sense if you are sick or run into any emergency situation. In case you cannot go to a class, you must send (or ask some one to send) an explanation message to the instructor no later than 24 hours after the class. For example, if you cannot go to a class on Wednesday, you need to send a message before 2:00pm the next day (i.e., Thursday).

  3. Readings
  4. Specific reading assignments will be posted in the schedule page.

  5. Assignments
  6. The assignments are designed to ensure that every student has a deep and precise understanding of the major core topics, thus the students are generally required to complete them independently. Discussion with others is allowed to the extent of helping understand the material. The purpose of student collaboration is to facilitate learning, not to circumvent it. The actual solution must be done by each student alone, and the student should be ready to reproduce their solution upon request. In any case, you must exercise academic integrity. Make sure that you have read the University Policy on Academic Integrity, especially the section on plagiarism.

    Late submission of an assignment would result in a reduced grade for the assignment, unless an extension has been granted by the instructor. An assignment is worth full credit at the beginning of class on the due date (later if an extension has been granted). It is worth at most 90% credit for the next 24 hours. It is worth 75% credit for the following 24 hours. It is worth 50% credit after that. If you need an extension, please ask for it (by sending email to the instructor) as soon as the need for it is known. Extensions that are requested promptly will be granted more liberally. You must turn in all assignments.

    Students should submit all assignments via Compass in PDF files. The scores of all assignments are also released in Compass.

  7. Midterm examination
  8. There will be a midterm exam in the middle (or later in the second half) of the semester. The purpose is to ensure that students have a good understanding of all the core IR topics. The questions in the exam will be similar or comparable to the questions in the assignments. It will be in the classroom, lasting for 75 minutes.

  9. The course project
  10. The purpose of the course project is to provide students an opportunity to study and work on a topic in-depth so as to obtain experience with research in IR or application of advanced IR technologies to develop an interesting novel application system. Group projects are allowed and encouraged. You will be asked to do a presentation of your course project and submit a written project report at the end of the semester. More details to be posted later.

  11. Grading
  12. Grading will be based on the following weighting scheme: