Part I: Graphs

Welcome to this course!

This course is about a technology called 'conceptual graphs'. This technology can be used to represent knowledge and meaning in a computer. The technology consists of a "formal language" in which we can express knowledge and meaning. In this course, we will be learning about that language, but not much about any particular implementation. We will be drawing graphs with pencil and paper where necessary, and we will learn to read conceptual graphs.


A simple conceptual graph could look like this:

It represents the phrase "Conceptual graphs". This is a very simple example, but conceptual graphs can scale to almost any size to express almost anything which we want to say.

Knowledge bases

A knowledge base, so far as conceptual graph-theory is concerned, consists of a number of things:

  • A number of conceptual graphs which express some of the knowledge which we have,
  • A type hierarchy of types which express the categories which we can talk about,
  • A relation hierarchy of relations which express the kinds of relationships we can have between types in our knowledge base,
  • A catalog of individuals which tells us the identity of each individual that appears in our knowledge base.

Knowledge bases are the means to representing knowledge and meaning. We will not be making reference to any particular knowledge base in this course. Instead, we will simply assume that all the graphs we draw are part of some larger knowledge-base which has the elements listed above.

Scope of conceptual graph-theory

Conceptual graphs as such are only a part of the overall theory of conceptual graphs: Other parts include:

  • type hierarchies,
  • relation hierarchies,
  • lambda expressions,
  • coreference,
  • contexts and nested graphs.

We will get back to all of these in due course. For now, it is important to bear this goal in mind: That we will be able to represent knowledge and meaning in a computer.


Next, we note some practical points before going on to the main material.

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