Geographic Knowledge Representation Methods Print
Greek version / Ελληνική έκδοση

 

Level: Optional postgraduate course of the spring semester (a 2hour lecture per week)

 

Prerequisite course: Geoinformation Theory

 

Course objectives: The main objective of the course is to present the existing methods for the representation of geographic knowledge in a computer. At first, the difference between the terms data, information and knowledge is addressed. The existent principal methods of knowledge representation are introduced, such as semantic nets and lattices. Also the importance of formalizing knowledge about the geographic space is presented, for solving interoperability problems among spatial data systems.

 

Course Content:

 

  • Introduction to knowledge representation – Historic Development.
  • Data-Information-Knowledge.
  • Geographic Knowledge - definition - characteristics.
  • First Order Logic.
  • Semantic Nets.
  • Frames.
  • Lattices.
  • Rule-based Systems.
  • Conceptual Graphs.
  • Formal Ontologies.
  • Ontology engineering.
  • NLP: Natural language processing.

 

Coordinator - Person in charge: Professor M. Kavouras

Teaching Assistants: M. Kokla, E. Tomai, A. Karalopoulos

 

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