16-04-2013, 04:50 PM
Knowledge Representation
Knowledge Representation.PPT (Size: 447 KB / Downloads: 189)
Representational adequacy
declarative, procedural
Inferential adequacy
manipulate knowledge
incorporate new knowledge
Semantic Data Models
High level model of model of conceptual model
Not tied to implementation concerns
Focus on
expressiveness
simplicity
concise
formality
Classes, Objects, Attributes, Values - Object Orientation
Classes describe common properties of objects
Objects may be physical or conceptual
Attributes are characteristics of objects
Values are specific measures of Attributes for specific instances
Objects or Instances
Refers to things identified in model of conceptual model
may be tangible (equipment, part, orders, squashed bananas)
may be mental constructs
Rule Representations
Rules are called productions
Rule have two parts
condition part, premise -> IF
action part ,conclusion-> THEN
The action can add a fact to the knowledge base, start a procedure or display a screen
Rule for understanding
Quantitative to Qualitative
qualitative language is easier to understand
interpretation of numerical data
make user feel comfortable with decision logic
If temperature > 200 and humidity is 85% then machine is slightly overheated