Teacher:
Lessons schedule: The course will be held in the following periods:
In addition there will some tutoring and laboratory hours. For the days April 14th-16th the timetable is the following:
For the second week, April 28th-30th the proposed timetable is the following:
For the third week, May 5th-7th the proposed timetable is the following:
For the fourth week, May 19th-21st the proposed timetable is the following:
Knowledge-intensive processes are more unstructured processes with a lot of involvements of users with their experience. These users need experience and knowledge at different levels for their work and decision making. Supporting such processes at their levels requires modelling and enacting several different forms of knowledge.
For connecting people to other knowledgeable people or providing access to relevant information mainly structural knowledge is used as meta-knowledge to support indexing and intelligent information retrieval. For preprocessing information etc. and even automatically derive and suggest possible solutions the knowledge itself has to be formally represented in order to allow automated reasoning.
For example, rule systems may support users during their decisions; knowledge can be used to define explicitly the goals and precondition of one task in order to constrain the process control flow etc. In general more explicit represented knowledge allows better support. But different forms of knowledge need different intuitive and adequate representations and inferences.
After completion of this module, the participants will be able to assess which kind of knowledge representation and reasoning is adequate and are able to develop appropriate knowledge-based systems. They can value the advantages of knowledge-based systems with respect to their costs.
Business Intelligence is concerned with supporting business decisions with facts. It supports business actors in turning data into knowledge that helps to make the right decisions. The module looks at different kinds of decisions (and hence requirements), at different kinds of data and different kinds of tools required to distill knowledge out of data.
This module is concerned with the acquisition, the representation and the inference of knowledge. Various forms of knowledge representation and inference techniques are analysed and discussed in detail. This course will include topics like
Course Material
Software and Tools
Exam Date A.Y. 2014/2015
Exam rules:
Exam Results