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A introduction to CommonKADS: structured knowledge engineering. Guus Schreiber www.commonkads.uva.nl. Activities in knowledge-system development. Business context modelling. Knowledge modelling. Communication modelling. System design. Why context modeling?.

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A introduction to commonkads structured knowledge engineering l.jpg

A introduction to CommonKADS: structured knowledge engineering

Guus Schreiber


Activities in knowledge system development l.jpg
Activities in knowledge-system development










Why context modeling l.jpg
Why context modeling?

  • Often difficult to identify profitable use of (knowledge) technology

  • Laboratory is different from the ''real'' world

  • Acceptability to users very important

  • Fielding into ongoing process not self evident

  • Often not clear what additional measures to take

How to analyze a knowledge intensive organization l.jpg
How to analyze a knowledge-intensive organization?

  • describe organization aspects:

    • opportunity/problems portfolio

    • business context, goals, strategy

    • internal organization:

      • structure

      • processes

      • people (staff: functional roles)

      • power and culture

      • resources (knowledge, support systems, equipment,…)

  • do this for both current and future organization

    • comparison, and first decisions on where to go

Worksheets organization model l.jpg
Worksheets Organization Model

Knowledge modelling l.jpg
Knowledge modelling

  • Specific type of conceptual modelling

    • Only gradual differences with “general” conceptual modelling

  • Knowledge modelling from scratch is time-consuming and difficult

    • Knowledge reuse is important theme

  • Patterns exist for types of problem-solving tasks

    • Base on typology of problem-solving tasks

Analytic versus synthetic tasks l.jpg
Analytic versus synthetic tasks

  • analytic tasks

    • system pre-exists

      • it is typically not completely "known"

    • input: some data about the system,

    • output: some characterization of the system

  • synthetic tasks

    • system does not yet exist

    • input: requirements about system to be constructed

    • output: constructed system description

Knowledge categories l.jpg
Knowledge categories

  • Task knowledge

    • goal-oriented

    • functional decomposition

  • Domain knowledge

    • relevant domain knowledge and information

    • static

  • Inference knowledge

    • basic reasoning steps that can be made in the domain knowledge and are applied by tasks

Domain knowledge l.jpg
Domain knowledge

  • domain schema

    • schematic description of knowledge and information types

    • comparable to data model

    • defined through domain constructs

  • knowledge base

    • set of knowledge instances

    • comparable to database content

    • but; static nature

Constructs for domain schema l.jpg
Constructs for domain schema

  • Concept

    • cf. object class (without operations)

  • Relation

    • cf. association

  • Attribute

    • primitive value

  • Rule type

    • introduces expressions => no SE equivalent

Inference l.jpg

  • fully described through a declarative specification of properties of its I/O

  • internal process of the inference is a black box

    • not of interest for knowledge modeling.

  • I/O described using “role names”

    • functional names, not part of the domain knowledge schema / data model

  • guideline to stop decomposition: explanation

Task knowledge l.jpg
Task knowledge

  • describes goals

    • assess a mortgage application in order to minimize the risk of losing money

    • find the cause of a malfunction of a photocopier in order to restore service.

    • design an elevator for a new building.

  • describes strategies (methods, PSMs) that can be employed for realizing goals.

  • typically described in a hierarchical fashion:

Assessment l.jpg

  • find decision category for a case based on domain-specific norms.

  • typical domains: financial applications (loan application), community service

  • terminology: case, decision, norms

  • some similarities with monitoring

    • differences:

      • timing: assessment is more static

      • different output: decision versus discrepancy

Example assessment task mortgage assessment l.jpg
Example assessment task:mortgage assessment

Assessment abstract match method l.jpg
Assessment: abstract & match method

  • Abstract the case data

  • Specify the norms applicable to the case

    • e.g. “rent-fits-income”, “correct-household-size”

  • Select a single norm

  • Compute a truth value for the norm with respect to the case

  • See whether this leads to a decision

  • Repeat norm selection and evaluation until a decision is reached

Template pattern for assessment task l.jpg
Template (pattern) for assessment task














Normen en beslisregels voor ww beoordeling l.jpg







ALS niet verzekerd of niet werkloos of niet voldoet aan wekeneis DAN geen WW

ALS wel wekeneis en niet jareneis DAN korte basisuitkering

ALS wel jareneis DAN loongerelateerde uitkering

Normen en beslisregels voor WW beoordeling

In applications typical task combinations l.jpg
In applications: typical task combinations

  • monitoring + diagnosis

    • Production process

  • monitoring + assessment

    • Nursing task

  • diagnosis + planning

    • Troubleshooting devices

  • classification + planning

    • Military applications

Summary l.jpg

  • Knowledge engineering is a specialized form of software engineering

  • CommonKADS: model-based approach to knowledge engineering

  • Reuse of task-specific knowledge models is important theme

  • Knowledge model often outlives application