Information Retrieval
Teaching personnel
Formalia
- Targeted audience
- DAI Hauptstudium with 12 credit points : Informatik der Systeme oder Bereich "D"
- Angewandte Informatik Master: AI MA
- Angewandte Informatik Bachelor: AI Schwerpunkt Medieninformatik: Erste Hälfte der Vorlesung (bis einschließlich Visualisierung), mit Übungen und Praktikum
- Komedia Bachelor: Erste Hälfte der Vorlesung, mit Übungen
Dates
Lectures
Date | Time | Place |
| Monday | 14:15 - 15:45 | LE/105 |
| Tuesday | 10:15 - 11:45 | LE/105 |
Tutorials
Date | Time | Place | Tutor |
| Monday | 16:00 - 18:00 | LE/105 | Dr.-Ing. Dipl.-Inform. Matthias Jordan |
| Friday | 10:00 - 12:00 | LC/137 | Dr.-Ing. Dipl.-Inform. Andrea Ernst-Gerlach |
Examination Dates
Exam
Date | Time | Place | Degree |
| 21. 07. 2010 | 10:00 - 11:30 | LF/310 | Bachelor AI |
Oral Exam
| Period | Place | Degree |
|---|---|---|
| 13.09.2010 - 16.09.2010 | LF/135 | Diplom AI |
Description
First tutorial: Fr., 16.4.2010. (depending on the group)
Information Retrieval (IR) deals with information search in purely structured data like e.g. fulltexts or multimedia databases. Popular applications are web search engines, digital libraries and multimedia archives (e.g. for images).
Due to the vagueness of the information need and the uncertain representation of the content of the stored objects, standard database techniques are not appropriate. Instead, the concepts have to be extended to deal with vagueness and uncertainty. As the major focus is on content-oriented search, special techniques for representing the content of text and multimedia objects are required.
This lecture introduces the underyling concepts of IR and illustrates them based on special application areas.
Content:
- A) Basic concepts (information cycle, evaluation)
- B) Representation of content (free text search, documentation languages, special logics)
- C) Models (classic models, models for multimedia documents)
- D) Implementation of IR systems (layer model, visualisation, access paths, algorithms)
- E) IR tasks (retrieval, filtering, categorisation, cross-language retrieval, text mining, summarization)
- F) Application areas (web search engines, multimedia digital libraries, IR and databases)
Lecture material
Besides the slides and the lecture notes, the following books and lecture notes are recommended:
-
R.
Baeza-Yates, B. Ribeiro-Neto: Modern Information Retrieval.
Addison Wesley.
(The chapter about user interfaces and visualisation is online.) - R. Belew: Finding Out About. A Cognitive Perspective on Search Engine Technology and the WWW. Cambridge University Press.
- Marti A. Hearst: Search User Interfaces. Cambridge University Press. (2009)
- Reginald Ferber: Data Mining und Information Retrieval. dpunkt Verlag . (earlier version)
- C. J. van Rijsbergen: Information Retrieval (HTML version of the book from 1979, but still worth reading)
Lecture notes
(The lecture notes only partialy cover the content of the lecture, some parts are available only as slides.)
- Appelt/Israel: Introduction to Information Extraction Technology
- Gianni Amati, Cornelis Joost Van Rijsbergen Probabilistic models of information retrieval based on measuring the divergence from randomness ACM Transactions on Information Systems (TOIS) 20, (4), 2002, pp. 357-389
- Norbert Fuhr: A Decision-Theoretic Approach to Database Selection in Networked IR . ACM Transactions on Information Systems
Links
Material for the tutorials
Für die Übung ist eine Anmeldung erforderlich. Bitte benutzen Sie das Anmeldeformular.
Arbeitsblätter
An dieser Stelle werden wöchentlich die Übungsaufgaben zum Download bereitgestellt. Die Lösungen sind dann als PDF über das Webformular hochzuladen.