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Core Lecture "Information Retrieval and Data Mining" WS 2011/12


Dr. Martin Theobald and Dr. Pauli Miettinen

Teaching Assistants

Sarath Kumar Kondreddi
Erdal Kuzey
Faraz Makari Manshadi
Niket Tandon
Tomasz Tylenda
Mohamed Yahya


News & Announcements

Schedule & Slides


Tests & Solutions

Tutoring Groups

The assignments to tutoring groups are now available.
(Last change: 2011.11.02 16:02. No more changes are possible.)


The lecture teaches mathematical models and algorithms that form the basis of search engines for the Web, intranets, and digital libraries, and for data mining and analysis tools. Information Retrieval and Data Mining are technologies for searching, analyzing and automatically organizing text documents, multi-media documents, and structured or semistructured data.


Students planning to attend the course should be familiar with basic models and methods from linear algebra (e.g. singular-value decomposition), probability theory and statistics (e.g. Bayesian networks and Markov chains), and combinatorics.

Requirements for Passing the Course

The requirements for passing the course and obtaining credit points are:

  1. You must convincingly present three correct solutions to the exercises in the tutoring group.
    In order to present an exercise in the tutoring groups, you must return the assignment sheet on the Thursday before the execises take place and have a correct solution for the exercise you intend to present.
  2. You must pass at least two out of three short tests that will be offered during the semester. The tests will be in written form, each with three or four questions that repeat material from the lecture and the assignments. Each test will last 45 to 60 minutes and will be on the following dates: November 17, December 20, and January 31.
  3. You must pass a final exam to be held on February 21 in written form.

Grading System

Your grades will be primarily determined by the final exam. You can earn bonus points that will improve your grade in the following ways, where one bonus point corresponds to a third mark in the German grading system (so that three bonus points will improve your grade from the final exam by a full mark, e.g., from 3.0 (C) to 2.0 (B) or from 2.7 (C+) to 1.7 (B+)).

  1. You can earn one bonus point by presenting a correct solution to one of the exercises in your tutoring group, in addition to the three presentations which are mandatory for passing.
  2. The tests will be assessed with one of the following coarse-grained grades: very good, pass, failed. Each test that is graded as very good will earn you one bonus point. You can earn up to 3 bonus points this way.


Further Reading

Background on Statistics and Probability Theory