Approaches to Knowledge Representation
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Approaches to Knowledge Representation

Simple relational knowledge

The simplest way of storing facts is to use a relational method where each fact about a set of objects is set out systematically in columns. This representation gives little opportunity for inference, but it can be used as the knowledge basis for inference engines.

  • Simple way to store facts.
  • Each fact about a set of objects is set out systematically in columns (Fig. 7).
  • Little opportunity for inference.
  • Knowledge basis for inference engines.

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Figure: Simple Relational Knowledge

We can ask things like:

  • Who is dead?
  • Who plays Jazz/Trumpet etc.?

This sort of representation is popular in database systems.

Inheritable knowledge

Relational knowledge is made up of objects consisting of

  • attributes
  • corresponding associated values.

We extend the base more by allowing inference mechanisms:

  • Property inheritance
    • elements inherit values from being members of a class.
    • data must be organised into a hierarchy of classes (Fig. 8).
http://users.cs.cf.ac.uk/Dave.Marshall/AI2/inherit.webp

Fig. 8 Property Inheritance Hierarchy

  • Boxed nodes — objects and values of attributes of objects.
  • Values can be objects with attributes and so on.
  • Arrows — point from object to its value.
  • This structure is known as a slot and filler structure, semantic network or a collection of frames.

The algorithm to retrieve a value for an attribute of an instance object:

  1. Find the object in the knowledge base
  2. If there is a value for the attribute report it
  3. Otherwise look for a value of instance if none fail
  4. Otherwise go to that node and find a value for the attribute and then report it
  5. Otherwise search through using isa until a value is found for the attribute.