Domain description grammar: application of linguistic semantics

ABSTRACT

Domain descriptions should represent more than the characteristics of data and the operations on it. They should be "semantic" in the sense that they may represent information such as the meanings of special terms used in the business, as well as goals and rules. ER models are often described as "semantic data models". However, the correspondence between ER and natural language is through syntactic rather than through semantic constructs. Conceptual modeling languages and knowledge representation techniques are more appropriate for representing domain meaning. Modern research in linguistics, semantics, and artificial intelligence provides valuable insight into basic issues regarding such representations. Domain descriptions must use languages based on generally-accepted linguistic and knowledge representation principles.

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.4 Knowledge Representation Formalisms and Methods
          Subjects: Representations (procedural and rule-based)

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE

  J. Computer Applications
  J.5 ARTS AND HUMANITIES
      Subjects: Linguistics

General Terms:
Languages