Class
Schedule:
Oct - Nov 2011, Room HSi3
https://online.tugraz.at/tug_online/lv.detail?clvnr=156319
Markus Strohmaier
Instructor: Markus Strohmaier
Adress: Inffeldgasse 21a, 2nd floor, Room IMO2152, 8010 Graz, Austria
e-mail: markus.strohmaier at@ tugraz.at (remove spaces, replace at@
with @), please start subject line with [707.009]
Students with special needs: If you need accomodation for any type of physical or learning disability, please contact me via e-mail to set up a meeting where we can discuss potential modifications for your participation.
This course aims to give students a basic understanding about the fundamental principles, concepts and challenges underlying knowledge management (KM). At the end of this course, students will have a thorough theoretical understanding of these issues, and the ability to relate and apply KM techniques and methods in the light of simple examples. Selected examples are used to illustrate the utility of knowledge management approaches in specific situations, but also to highlight current gaps between KM theory and practice.
Students need to take an exam. For more information on taking the exam, please read the according policy at the end of this page.
Note to students: This schedule is preliminary, changes will likely be made. Additional/other readings may be assigned. Access credentials for protected resources will be handed out in class.
Note to instructors: All teaching materials on this website are available for use under a Creative Commons Attribution-Noncommercial-Share Alike 2.0 Austria License, except for cited material / where noted otherwise. Access to protected areas is only available to enrolled students.
Week
|
Date
|
Title, Slides | Comments and Links |
1
|
3.10.2011
(HS i3, 12:15) |
Overview and Motivation (slides) |
In this class, we will discuss the course organization and give a basic motivation for and introduction to the course. |
2
|
5.10.2011
(HS i3, 12:15) |
Knowledge Acquisition I (slides) |
What is knowledge? What forms of knowledge can we identify? We will discuss some basic distinctions and characterizations. Readings: D. Kirsh, When is information explicitly represented?, Information, Language and Cognition - The Vancouver Studies in Cognitive Science.: 340--365, 1990. [Protected Access] |
3
|
10.10.2011 (HS i3, 12:15)
|
Knowledge Organization (slides) |
How can knowledge be organized? We will discuss some basic principles of knowledge organization, such as categorization, taxonomies, ontologies and concept systems. Readings: C.B. Mervis and E. Rosch, Categorization of Natural Objects, Annual Review of Psychology 32 89--115, 1981 [Protected Access]
|
4
|
12.10.2011 (HS i3, 12:15)
|
Categorization & Formal Concept Analysis (slides) |
How can categorization be formalized?
|
5
|
18.10.2011
(HS i3, 12:15) |
Broad Knowledge Bases (slides) |
What kinds of broad knowledge bases exist? We will discuss different forms of knowledge bases and representations, such as metadata, wordnet, framenet, cyc, openmind and others. Readings: T. Berners-Lee and J. Hendler and O. Lassila, The semantic Web, Scientific American, 284 (5) 2001. |
6
|
20.10.2011 (HS i3, 11:15)
|
Participative Knowledge Acquisition Methods (slides) |
How can knowledge be acquired from users in a way that makes knowledge amenable to computation and/or analysis? Readings: L. von Ahn, Games with a Purpose, Computer, 39(6): 92--94, 2006
|
7
|
24.10.2011 (HS i3, 12:15)
|
Latent Semantic Analysis |
Latent Semantic Analysis Readings: An Introduction to Latent Semantic Analysis: http://lsa.colorado.edu/papers/dp1.LSAintro.pdf
|
8
|
25.10.2011
(HS i3, 14:15) |
Probabilistic Topic Models (slides) |
Topic Modeling Matlab Toolbox Weblink Readings: Probabilistic Topic Models SteyversGriffithsLSABookFormatted.pdf
|
9
|
2.11.2011
(HS i3, 13:15) |
Inductive Concept Learning and ILP (slides) |
Introduction to Inductive Concept Learning and ILP. Readings: Nada Lavrac and Saso Dzeroski:
Inductive Logic Programming: Theory and Applications: (Chapters 1.,2.
and 3.2: Bookwebsite
+ pdf)
|
10
|
7.11.2011 (HS i3, 10:15) |
Multimedia & Semantic Metadata (slides) |
In this class, we will discuss different forms of semantic annotation of multimedia documents. Guest Lecture: Mathias Lux |
11
|
9.11.2011 (HS i3,
11:00) |
Association Rule Learning (slides) |
Readings: Data Mining: Concepts and Techniques (Chapters 5.1 - 5.2.4, protected access) An introduction to association rules and association rule learning. |
12
|
15.11.2011 |
Evaluation Strategies and Methods (slides)
|
In this lecture, we will talk about case studies involving the evaluation of knowledge bases. Guest Lecture: Christian Körner
|
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|
|
|
13
|
18.11.2011
(HS i7, 14:00) |
Final Exam |
The final exam will take place in HSi7, 14:00 - 16:00. All you need to bring is a pen and your student ID. |
There are two different ways of obtaining a grade for this course:
To pass either exam (written/oral), you need to have in-depth knowledge about the entire course contents (all lectures including guest lectures, see slides) and the accompanying literature (see papers).
This policy is preliminary. Changes will likely be made.