Network-Based Analysis for Discovering Semantic Redundancy

Guodong Wang, Chao Gao, Ye Yuan, Zili Zhang

Research output: Contribution to journalArticlepeer-review

Abstract

The efficiency of semantic reasoning can be improved through constructing the semantic ontology reasonably and reducing the redundant information in the process of reasoning. It is a feasible method to reveal the reason of the redundant information in the process of reasoning through analyzing the dynamic changes of an ontology structure and the important role of nodes in an ontology. Taking AGROVOC ontology network as an example, this paper provides qualitative analyses based on the reasoning mechanism of semantic web for understanding the redundant information. Meanwhile, some quantitative measurements from the perspective of complex network are provided in order to identify the core concepts in a semantic web, and further to solve the problem of redundant information. Experimental results show that the reasoning of semantic web and the rationality of ontology construction can be quantitatively analyzed from the perspective of complex network, which provides a new measurement to optimize the design of ontology and improve the efficiency of reasoning in the semantic web.

Original languageEnglish
Pages (from-to)58-65
Number of pages8
JournalComplex Systems and Complexity Science
Volume14
Issue number1
DOIs
StatePublished - 1 Mar 2017
Externally publishedYes

Keywords

  • AGROVOC
  • Complex networks
  • Reasoning
  • Redundancy

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