Course: 707.009 Foundations of Knowledge Management

"Knowledge Acquisition and Organisation"

(707.009 Grundlagen des Wissensmanagements)

Graz University of Technology Fall 2009/10

Class Schedule: November 2009 - January 2010, Rooms HSi12 and HS Modul

https://online.tu-graz.ac.at/tug_online/lv.detail?clvnr=138482
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.

Announcements:

About the course:

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.

Grading:

Students need to take a final exam, which will take place at the end of the semester. For more information on taking the exam, please read the according policy at the end of this page.

Preliminary course schedule and weekly readings:

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
20.11.2009

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
23.11.2009

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
24.11.2009

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
30.11.2009

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.

5
1.12.2009

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

 

 

6
7.12.2009

Categorization & Formal Concept Analysis

(slides)

How can categorization be formalized?

Readings: Chapters 1 - 2.3.2, Formal Concept Analysis: Methods and Applications in Computer Science, Bernhard Ganter, Adapted and extended by Gerd Stumme, Summer 2003



7
14.12.2009

Latent Semantic Analysis

(slides1, slides 2)

Latent Semantic Analysis

Readings: An Introduction to Latent Semantic Analysis: http://lsa.colorado.edu/papers/dp1.LSAintro.pdf

 

8
15.12.2009

Probabilistic Topic Models

(slides)

Topic Modeling

Matlab Toolbox Weblink

Readings: Probabilistic Topic Models SteyversGriffithsLSABookFormatted.pdf
Optional: Topics in Semantic Representation topicsreview.pdf

9
11.1.2010

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
12.1.2010

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 by Mark Kröll.

11
18.1.2010

Multimedia & Semantic Metadata

(slides)

In this class, we will discuss different forms of semantic annotation of multimedia documents.

Guest Lecture: M. Lux, Klagenfurt University

12

19.1.2010

Evaluation Strategies and Methods

(slides)

In this lecture, Christian Körner will talk about to case studies involving the evaluation of knowledge bases.

 

13
25.1.2010

 

Knowledge Management & the Web

(slides1, slides2)

 

In this class, we will discuss recent trends, technologies and developments in knowledge management on the web, in particular "social" web technologies for and approaches to knowledge management.

 

14
28.1.2010

Final Exam

The final exam will take place in HSi12, 14:00 - 16:00. All you need to bring is a pen and your student ID.

 

Policy for Exams:

There are two different ways of obtaining a grade for this course:

  1. There will be one written exam at the end of each semester (fall/winter and summer). Examination dates for written exams will be announced via TUGonline. There is no limit on the number of students that can take the written exam.
  2. In addition to written exams, oral exams will be offered at the beginning and at the middle of each semester. In case you want to take an oral exam, please contact me at least 4 weeks ahead of time to arrange for a date. Please note that there is limited availability for oral exams, and they are available on a request / first come first serve basis only.

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.