Knowledge Engineering and Business Intelligence

Lectures Dates Remaining:

Tuesday, 14th of May, 10 - 13 (AB2)
Wedndesday, 15th of May, 10 - 13 (AB1)
Monday, 3rd of June, 14 - 18 (AB2)
Tuesday, 4th of June, 10 - 13 (AB2)
Wedndesday, 5th of June, 9 - 13 (AB1)

Teachers:

Knut Hinkelmann
Holger Wache

ESSE3 Link

Knowledge Engineering and Business Intelligence - AY 2018/2019

Supporting Knowledge-Intensive Processes

Knowledge-intensive processes are more unstructured processes with a lot of involvements of users with their experience. Supporting such processes at their levels requires modelling and enacting several different forms of knowledge. 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.

Course Contents

Introduction: Knowledge in processes
Decision Tables
Rules
- Textual represented rule (i.e. Horn clauses)
- Forward and backward chaining
- Data-driven and Goal-oriented
- Negation-as-failure
Object-centred Systems
- F-Logic/Objectlogic
Fuzzy Logic
Business Intelligence & Data Warehouse
Reporting and Data Analysis
Machine Learning: Learning Decision Trees
Case-Based Reasoning
Neuronal Networks

ke-3-logic_programming.pdf

Course Material

Organisation

Lecture “Introduction”
- Slides: Introduction
- Davenport, T. H. (2010). Process Management for Knowledge Work. In J. vom Brocke & M. Rosemann (Eds.), Handbook on Business Process Management 1 (pp. 17–36). Berlin, Heidelberg: Springer.

Lecture “Decision Tables”
- Slides: Decision Tables
- Download: Camunda Workflow and Decision Modeler
- Template: Decision Table (Excel)
- Exercise: Decision Modeling for the Admission Process
- Reading: Introduction into DMN

Lecture “Rule-based Systems”
- Slides: Rule-based Systems
- Reasoning example: ancestor
- Exercise: University and Solution
- Exercise: Family and Solution
- Exercise: Further small examples and Solution
- Exercise: Mini Sudoku and Solution
- Home Work with Solution
- Nice browser-based Prolog Engine

Lecture “Forward- and Backward Chaining”
- Slides: Forward- and Backward Chaining

Lecture “Objectlogic”
- Slides: Objectlogic
- Exercise: Family and Solution
- Exercise: ObjectLogic vs Prolog and Solution
- Homework

Lecture “Fuzzy logic”
- Slides: Fuzzy Logic
- Exercise: Fuzzy Sets and Solution
- Exercise: Fuzzy Set Operations and Solution
- Exercise: Credit Analysis