This is version 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 . It is not the current version, and thus it cannot be edited.

Back to current version Restore this version

Printer Problems Diagnosis#

This small demo example shows the basic functionality of KnowWE and its corresponding knowledge representations for the formalization of diagnostic knowledge.

We build a knowledge base for deriving the reasons for the faults of an imaginary printer.

Set-Up#

Annotate Wiki Articles#

Every article containing knowledge of the printer example needs to be tagged in a special manner. We choose the tag name Printer_Demo and we insert the annotation

%%Package Printer_Demo

into every particular article containing knowledge.

Define the Knowledge Base Center#

In general, the knowledge base can be distributed across many wiki articles (each of them tagged with Printer_Demo). Therefore, we need to define a place where all knowledge elements are collected into a single knowledge base. For this, we use the KnowledgeBase markup in the following manner:

%%KnowledgeBase 
  Printer Fault Diagnosis Demo 
  @author: joba
  @version: 1.0
  @uses: Printer_Demo
%

By inserting the markup the following center is provided:

Terminology#

In the first step we need to define the terminology of the planned system, i.e., the inputs (user entries) and the outputs (derived solutions).

Derivation Knowledge#

After the definition of the terminology we need to define knowledge elements that implement the derivation and dialog behavior of the knowledge base. For that, d3web/KnowWE provides a number of alternatives ranging from scoring rules, decision trees to set-covering models. In this tutorial we show how to implement the derivation knowledge as a DiaFlux flowchart model.

• DiaFlux implementation

Testing the Knowledge Base#

In the next step, we test the knowledge base by using the