Bridging real world semantics to model world semantics for taxonomy based knowledge representation system

Ju H. Kwon, Chee Yang Song, Chang J. Moon, Doo Kwon Baik

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

As a mean to map ontology concepts, a similarity technique is employed. Especially a context dependent concept mapping is tackled, which needs contextual information from knowledge taxonomy. Context-based semantic similarity differs from the real world similarity in that it requires contextual information to calculate similarity. The notion of semantic coupling is introduced to derive similarity for a taxonomy-based system. The semantic coupling shows the degree of semantic cohesiveness for a group of concepts toward a given context. In order to calculate the semantic coupling effectively, the edge counting methods is revisited for measuring basic semantic similarity by considering the weighting attributes from where they affect an edge's strength. The attributes of scaling depth effect, semantic relation type, and virtual connection for the edge counting are considered. Furthermore, how the proposed edge counting method could be well adapted for calculating context-based similarity is showed. Through experimental results are provided for both edge counting and context-based similarity. The results of proposed edge counting were encouraging compared with other combined approaches, and the context-based similarity also showed understandable results. The novel contributions of this paper come from two aspects. First, the similarity is increased to the viable level for edge counting. Second, a mechanism is proviede to derive a context-based similarity in taxonomy-based system, which has emerged as a hot issue in the literature such as Semantic Web, MDR, and other ontology-mapping environments.

Original languageEnglish
Pages (from-to)296-308
Number of pages13
JournalJournal of Computer Science and Technology
Volume20
Issue number3
DOIs
Publication statusPublished - 2005 May 1

Fingerprint

Knowledge representation
Taxonomies
Knowledge Representation
Taxonomy
Semantics
Counting
Semantic Similarity
Ontology
Model
Attribute
Ontology Mapping
Semantic Web
Similarity
Calculate
Context
Weighting
Scaling
Dependent
Experimental Results

Keywords

  • Context-based similarity
  • Edge counting
  • Semantic coupling
  • Semantic similarity
  • Weighting attributes
  • WordNet

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Hardware and Architecture
  • Software

Cite this

Bridging real world semantics to model world semantics for taxonomy based knowledge representation system. / Kwon, Ju H.; Song, Chee Yang; Moon, Chang J.; Baik, Doo Kwon.

In: Journal of Computer Science and Technology, Vol. 20, No. 3, 01.05.2005, p. 296-308.

Research output: Contribution to journalArticle

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