Chinese fuzzy ontology mapping based on support vector machine

Jie Liu*, Yun Ma, Shiping Tang, Peng Lu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Taking into account that fuzzy ontology mapping has wide application and cannot be dealt with in many fields at present, a Chinese fuzzy ontology model and a method for Chinese fuzzy ontology mapping are proposed. The mapping discovery between two ontologies is achieved by computing the similarity between the concepts of two ontologies. Every concept consists of four features of concept name, property, instance and structure. First, the algorithms of calculating four individual similarities corresponding to the four features are given. Secondly, the similarity vectors consisting of four weighted individual similarities are built, and the weights are the linear function of harmony and reliability. The similarity vector is used to represent the similarity relation between two concepts which belong to different fuzzy ontolgoies. Lastly, Support Vector Machine (SVM) is used to get the mapping concept pairs by the similarity vectors. Experiment results are satisfactory.

Original languageEnglish
Pages (from-to)134-144
Number of pages11
JournalChina Communications
Volume9
Issue number3
Publication statusPublished - 15 Mar 2012

Keywords

  • Fuzzy knowledge representation
  • Fuzzy ontology mapping
  • SVM
  • Similarity aggregation

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