Information Retrieval

General Information

This web page gives information on the lecture 'Information Retrieval' which is held during the winter term 2020/2021 by Andreas Nürnberger. A moodle link will be provided, which will contain all the necessary information and content of the course and will be updated regularly. Please note, that this course will be online only!

Moodle link: https://elearning.ovgu.de/course/view.php?id=8756

The enrolment key will be sent to students via email after they enrol via LSF!

We have already shared the enrolment key (on 23rd Oct '20) with students who registered by LSF.

If you have registered in LSF after 23rd Oct and did not get the enrolment key by email, please write to sanket.joshi@st.ovgu.de for Moodle enrolment key.

Students who are yet to register and get login details to Moodle need not worry, we will record the lectures.

Exercises till 15th Nov 2020 (enrolment period) will be recorded.


Information retrieval focuses on obtaining, extracting or mining information from a large collection of unstructured data, e.g. in form of text documents, images or videos. Information retrieval concepts are applied in web search engines, digital libraries and multimedia archives such as image and video databases. In this course the foundations of information retrieval will be introduced and illustrated on some specific application areas.

Master students, please note that this course is 5CP only!

Requirements for Participation in the Final Exam

All students are required to participate in the exercise classes. Every week, there will be an assignment sheet that will be handed out one week in advance. This sheet has to be prepared by every student and will be discussed in class. There are two different types of exercise tasks: theoretical tasks and a programming task. The programming assignments can be solved in small groups of up to three students and must be sent in before the respective deadline. Prerequisites for a written exam and a 'Schein' is fulfillment of the following criteria:

  • at least 66% of individual votes for all theoretical tasks,
  • at least  66% of the group programming task (can be done in groups- 4-5 students per group)
  • at least two presentations of a solution in front of the class.

For acquiring the "Schein" you have to write and pass the exam.

A general reminder: In accordance with the examination rules, we offer each student exactly one examination date (oral or written) each term. The registration for a follow-up examination is only possible in the next term (i.e. after 6 months). As soon as a student has registered for an exam, either by using the LSF for written exams or by filling in the information on an examination list for oral exams (or filling out a registration form), this is counted as the agreed examination date. If it is cancelled, the rule above applies.

Dates and Rooms

The dates and times are not final, yet! Please wait until the registration phase starts! (19th of October 2020)

  Time Start Room
Lecture Mon, 15:00 - 17:00 26.10.2020 Zoom link (Moodle)

Exercise (1st group

&      5th group)

Mon, 9:00 - 11:00 02.11.2020 Zoom link (Moodle)
Exercise (2nd group) Wed, 11:00 - 13:00 04.11.2020 Zoom link (Moodle)
Exercise (3rd group) Tue, 17:00 - 19:00 03.11.2020 Zoom link (Moodle)
Exercise (4th group) Thu, 11:00 - 13:00 04.11.2020 Zoom link (Moodle)
Written Exam tba tba tba

 Please register for the exercises via LSF! (opens on 19th of October 2020)

 

Teaching Staff

If you have any questions about the lecture or the exercises, please contact us via e-mail:

Materials

Will be provided in Moodle (link to be given).

Additional Materials

Literature

  • Introduction to Information Retrieval, C.D. Manning, P. Raghavan, H. Schütze, Cambridge University Press, 2008. (Online-Version)
  • Search User Interfaces, Marti Hearst, Cambridge University Press, 2009. (Online-Version)
  • Soft Computing in Information Retrieval, Fabio Crestani and Gabriella Pasi, Physica Verlag, 2000.
  • Modern Information Retrieval, Ricardo Baeza-Yates and Berthier Ribiero-Neto, Addison Wesley, 1999.
  • Foundations of Statistical Natural Language Processing, Chris Manning and Hinrich Schütze, MIT Press, Cambridge, MA, 1999.
  • Information Retrieval: Data Structures and Algorithms, William B. Frakes and Ricardo Baeza-Yates, Prentice-Hall, 1992.

Last Modification: 28.10.2020 - Contact Person:

Sie können eine Nachricht versenden an: Prof. Dr.-Ing. Andreas Nürnberger
Sicherheitsabfrage:
Captcha
 
Lösung: