Title | Knowledge Management (KM) |
Type of course | Lecture and practical exercise |
Level | Master |
ECTS points | 6 |
SWS | 4 |
Language | English* |
Time and place of lectures | Mondays, 12:00-13:30, A 5, 6 Bauteil C - C 014 |
Time and place of exercises | Wednesdays, 13:45-15:15, A 5, 6 Bauteil C - C 014 |
Lecturer | |
Teaching Asssistant |
*Can be changed upon agreement of all participants
First appointment:
- 14.02.2011 (lecture)
- 23.02. (exercise) (changed on 14.02.2011)
Preliminaries:
- basic programming skills
Grading is based on:
- Exercises (30%)
- Written exam (70%)
For more details attend to the first lecture on Monday, 14.02.2011.
Content of the Lecture
Many modern enterprises, especially in highly developed countries depend on the corporate and the individual knowledge of their employees. Knowledge is the driving force for innovation and a precondition for successful product development and operation. This knowledge, especially the individual knowledge, however is often in danger of not being systematically used or even being lost as people leave an organization. Knowledge Management(KM) aims at reducing this problem by methods for systematically identifying, formalizing, sharing and using knowledge across an organization.
This course approaches Knowledge Management from a technological point of view focussing on techniques from computer science that support the identification, extraction, formalization, sharing and use of knowledge in an organization. It is organized in five parts:
- Introduction
- Knowledge Search and Discovery
- Building Knowledge Repositories
- Digital Socialization and Collaboration
- Creativity and Problem Solving
Dates and Topics
Lecture plan:
Date | Topic | Material (PDF) | Exercises (PDF) |
|---|---|---|---|
Introduction | |||
14.02. | Knowledge Management I | – | |
21.02. | Knowledge Management II | ||
Knowledge Search & Discovery | |||
28.02. | Information Retrieval I | ||
07.03. | Information Retrieval II | ||
14.03. | Data Mining I (Clustering) | ||
21.03. | Data Mining II (Classification) | Exercise05 [updated on 23.03.] - texts.arff.zip | |
Building Knowledge Repositories | |||
28.03. | Information Extraction I | ||
04.04. | Information Extraction II | ||
11.04. | Knowledge Repositories | ||
18.04. - 29.04 | Easter Holidays | ☕ | ☕ |
Digital Socialization and Collaboration | |||
02.05. | Web 2.0 and Enterprise 2.0 | ||
09.05 | Social network Analysis | Exercise10 (connected_graph.gml [right click=>save as…]) | |
Creativity and Problem Solving | |||
16.05. | e-Learning and Communities of Practice | ||
23.05. | Crowdsourcing | ||
30.05. | Lecture Canceled There will be an exercise lesson on wednesday | ☕ | ☕ |
10.06 | Final Exam | 11 am – 12:30 pm A5 B243 | Good Luck! |
Exercise Sheets
The exercise sheets can be worked on individually or in teams of two persons. The exercises will be released every Monday on this page and the solutions must be submitted within the following nine days. The official deadline is Wednsdays until 13:45 p.m. Solutions can be submitted in one of the following ways:
- Bring them to the exercise (preferred)
- Send the solutions to Johannes Knopp if you cannot attend to the exercise or submitting via email is required (PDF format only)
Every solution needs to contain the names and email addresses of its editors. Submissions after 13:45 p.m. won't be considered. When you send the solution via email the subject should look like "ex #, name1[, name2]" with # being replaced by the exercise's number.
Forum and Mailing List
We have a forum, where questions concerning the lecture and the exercises can be discussed. Students can log in with their RUM's name and password (click on "Anmelden" on the top right). There is no need to create a separate forum account. Students of other universities, please write an E-Mail (Name, Uni, Major) to the exercise instructor.
Further, we provide a mailing list at lski-km-stud(at)mailman.uni-mannheim.de. Please use the following website to register https://mailman.uni-mannheim.de/mailman/listinfo/lski-km-stud.