Information Retrieval
General Information
This web page gives information on the lecture 'Information Retrieval' which is held during the winter term 2018/2019 by Andreas Nürnberger. It will be constantly updated during the course.
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 votes for all theoretical tasks,
- at least 33% of the programming task and
- 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
Time | Start | Room | |
Lecture | Tue, 15:00 - 17:00 | 16.10.2018 | G22A-013 |
Exercise (1st group) | Tue, 9:00 - 11:00 | 23.10.2018 | G22A-211 |
Exercise (2nd group) | Fri, 9:00 - 11:00 | 26.10.2018 | G22A-217 |
Exam | Tue, 08:00 - 10:00 | 12.02.2019 | HS 1 |
Teaching Staff
If you have any questions about the lecture or the exercises, please contact us via e-mail:
- Andreas Nürnberger
E-Mail: andreas.nuernberger@ovgu.de - Michael Kotzyba
E-Mail: michael.kotzyba@ovgu.de - Afra'a Ahmad Alyosef
E-Mail: afraa.ahmad-alyosef@ovgu.de
Materials
Lecture Slides
- Introduction to IR
- Document Pre-Processing
- Indexing
- Vector Space Model
- Probabilistic information retrieval
- LSI
- Evaluation
- Search User Interfaces
- Web Search & Link Analysis
- Crawling
Exercise Sheets
- Assignment 01 (until 23. Oct. resp. 26. Oct. 2018)
- Assignment 02 (until 30. Oct. resp. 02. Nov. 2018)
- Assignment 03 (until 06. Nov. resp. 09. Nov. 2018)
- Assignment 04 (until 13. Nov. resp. 16. Nov. 2018)
- Assignment 05 (until 20. Nov. resp. 23. Nov. 2018)
- Assignment 06 (until 27. Nov. resp. 30. Nov. 2018)
- Assignment 07 (until 04. Dec. resp. 07. Dec. 2018)
- Assignment 08 (until 11. Dec. resp. 14. Dec. 2018) Afterwards: Repetition of Assignment 01
- Assignment 09 (until 18. Dec. resp. 21. Dec. 2018)
- Assignment 10 (until 08. Jan. resp. 11. Jan. 2019)
- Assignment 11 (until 15. Jan. resp. 18. Jan. 2019)
- Assignment 12 (until 22. Jan. resp. 25. Jan. 2019)
Programming Task
- Programming Task (until 20. Dec. 2018, 08:00 a.m.)
Additional Material
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.