A method for semantics-based conceptual expansion of ontology

ABSTRACT

For the past few years, automatic Ontology construction and expansion is one of the most important research subjects in the field of knowledge engineering. Compared with the traditional Term Frequency method, we propose a semantics-based method to extract concepts from a large corpus of text documents and expand the concepts of the known Ontology based on the semantic relations between two terms. The proposed method explores how to identify the candidate concepts, and how to give suggestions to knowledge engineers on where the concepts should be inserted in a given Ontology. The effectiveness of the proposed approach is demonstrated by experiments on a Traditional Chinese Medicine text corpus.

REFERENCES

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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:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.1 Content Analysis and Indexing

  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.4 Knowledge Representation Formalisms and Methods
          Subjects: Semantic networks; Relation systems

General Terms:
Algorithms, Design