Information Retrieval
General Information
This web page provides information on the course "Information Retrieval" (winter term 2016/2017). The updates of this web page will be done through the course after each lecture.
Information retrieval focuses on obtaining, extracting or mining information from a collection of often unstructured resource of text documents, images or videos. Information retrieval consept is applied in internet search engines, digital libraries and multimedia archive like image and vedio-databases. In this lectures the basis of information retrieval will be introduced and illustrated based on some specific application areas.
Requirements for Participation in the Final Exam
For the practice part there are exercise sheets. These exercises will be voted by everyone of the participants. A voting shows whether a paticipant is ready to present a solved task in front of the class. The solutions will be discussed, i.e., they do not have to be the full right solutions, but it should reflect that the participant at least has been worked in depth to figure out the solution.
In addition to the theoretical practice, there are programming tasks (assignments) that will be submitted and evaluated with points. These tasks should be processed in groups of 3-4 students. The deadline for submission will be announced for each assignment (usually a time of two or three weeks is determined to achive each task).
The requirements for participation in the final exam (oral or written) are:
- at least 50% of all programming points,
- at least 66% of votes for all other exercise tasks and
- at least one time presentation of a solution in front of the class.
For "Schein" you have to write and pass the exam.
Dates and Rooms
Time | Start | Room | |
Lecture | Thu 15:15 - 16:45 o'clock | 13.10.16 | G22A-105 |
Exercise (1st group) | Monday 11:15 - 12:45 o'clock | 17.10.16 | G05-307 |
Exercise (2nd group) | Wednesday 9:15 - 10:45 o'clock | 26.10.16 | G05-211 |
Exam | tba | tba | tba |
The date to have a look at your exam (from 28.07.2017), in order to know, what you have made right and wrong is 06.10.2017, 10 a.m., room G29-128.
Teaching Staff
If you have any questions about the lecture or the exercises, please contact us via e-mail:
Lecture:
Exercise:
Materials
Lecture Slides
- Introduction
- Document Pre-Processing
- Indexing
- The Vector Space Model
- Probabilistic information retrieval
- LSI
- Evaluation
- Search User Interfaces
- Web Search & Link Analysis
- Web Search - Crawling
Exercise Sheets
- Assignment sheet 1 (until 17. Oct. 2016)
- Assignment sheet 2 (until 24. Oct. 2016 respectively 26. Oct. 2016)
- Assignment sheet 3 (until 07. Nov. 2016 respectively 09. Nov. 2016)
- Assignment sheet 4 (until 14. Nov. 2016 respectively 16. Nov. 2016)
- Assignment sheet 5 (until 21. Nov. 2016 respectively 23. Nov. 2016)
- Assignment sheet 6 (until 28. Nov. 2016 respectively 30. Nov. 2016)
- Assignment sheet 7 (until 05. Dec. 2016 respectively 07. Dec. 2016)
- Assignment sheet 8 (until 12. Dec. 2016 respectively 14. Dec. 2016)
- Assignment sheet 9 (until 02. Jan. 2017 respectively 04. Jan. 2017)
- Assignment sheet 10 (until 09. Jan. 2017 respectively 11. Jan. 2017)
- Assignment sheet 11 (until 16. Jan. 2017 respectively 18. Jan. 2017)
- Assignment sheet 12 (until 23. Jan. 2017 respectively 25. Jan. 2017)
Programming Tasks
- Programming Task 1 (until 01. Dec. 2016)
- Evaluation for the Programming Task 1
- Programming Task 2 (until 15. Dec. 2016)
- Evaluation for the Programming Task 2
- To achieve an additional credit point (i.e. to get 6 credit points instead of 5) you have to solve additional programming task (deadline 19 Jan. 2017), that is:
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.