Information Retrieval and Data Mining

• 23.10.2019: First assignment is out!
• 30.10.2019: Slides from Lecture 02 updated.
• 30.10.2019: First assignment is due today at the lecture by 16:15!
• 05.11.2019: Hints added to Assignment 2!
• 15.11.2019: Clarifications added to Assignment 4 Problem 3.
• 26.11.2019: Tutorial presentation bonuses introduced - see Google Groups!
• 09.03.2020: Final Exam grades out - check here. Congrats! :)
• 09.03.2020: Final Exam inspection will be on the 12th of March. Check email in Google group for details.
• 09.03.2020: The re-exam topics will largely be based on those in the assignments and the first exam.
• 06.05.2020: The re-exam date has been decided (see below).
• 14.05.2021: Re-exam grades out - check here. Congrats! :)

Good knowledge of undergraduate mathematics (linear algebra, probability theory) and basic algorithms.

After you receive the assignment sheet, you solve the problems (individually) at home, and submit them on the appointed dates to the TAs before the lecture (by 16:15). During the tutorial sessions, the TAs will ask some of you to present your solutions. Every student must present their solutions at least 2 times during the semester. The TAs will also help in clarifying your answers. Your submitted sheets will be graded and handed back to you at the end of the session.

To do the exercises, you have to study the required reading material and go through the slides.

We do not allow plagiarism. The first time you are caught, you will receive 0 points for the specific assignment. The second time, you will be de-registered from the course. 

The overall grade will be the best result of the end-term and a re-exam (there will be no further attempts). There will be no mid-term exams. The final exam is closed-book and no discussion is allowed.

To participate in the final written exam, the following prerequisites are required:

• Submit ALL 14 assignments
• Obtain 50% or more on average over all assignments (80% or more on average will fetch you a bonus point, that results in one grade point jump (if possible) in the final exam)
• Present solutions at least 2 times in the tutorials

We will use the following primary textbooks.

For Probability and Statistics,

• Larry Wasserman: All of Statistics, Springer, 2004.

For Data Mining,

• Charu Aggarwal: Data Mining - The Textbook, Springer, 2015.
• Mohammed J. Zaki and Wagner Meira Jr: Data Mining and Analysis, Cambridge University Press, 2014.

For Information Retrieval,

• Chris Manning, Prabhakar Raghavan, and Hinrich Schütze: Introduction to Information Retrieval, Cambridge University Press, 2008.
• ChengXiang Zhai and Sean Massung: Text Data Management and Analytics, Morgan & Claypool, 2016

These and additional references are available in the library:

• http://www.infomath-bib.de/tmp/vorlesungen/info-core_information-retrieval-and-data-mining.html