Comprehensive Calculation of Semantic Similarity of Ontology Concept Based on SA-BP Algorithm
Computer Science

Computer Science ›› 2020, Vol. 47 ›› Issue (1): 199-204.doi: 10.11896/jsjkx.181202351

• Artificial Intelligence • Previous Articles     Next Articles

Comprehensive Calculation of Semantic Similarity of Ontology Concept Based on SA-BP Algorithm

XU Fei-xiang1,YE Xia1,LI Lin-lin1,CAO Jun-bo1,WANG Xin2   

  1. (Academy of Combat Support,Rocket Force University of Engineering,Xi’an 710025,China)1;
    (Information Systems Department,University of Maryland,Baltimore,Maryland 21250,USA)2
  • Received:2018-12-18 Published:2020-01-19
  • About author:XU Fei-xiang,born in 1995,postgra-duate.His main research interests include ontology integration and semantic network;YE Xia,born in 1977,Ph.D,associate professor.Her main research interests include database technology and computer network.
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (61702525).

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Abstract: There are heterogeneous problems in indicators that are established by different combat forces when evaluating and testing command information systems,which leads to great difficulties in information interaction and data sharing.In order to achieve mapping and integration of indicator’s ontology-concept,building a unified global indicator ontology tree is an effective solution.In this case,the accuracy of similarity calculation for ontology-concept becomes crucial.Aiming at the problem of low accuracy in the existing ontology-concept similarity calculation model,a comprehensive simi-larity calculation model based on BP neural network algorithm which is improved by Simulated Annealing (SA-BP),was proposed.This paper first improved the classical similarity calculation models based on semantic distance,information content and conceptual attribute.Besides,a similarity calculation model in view of concept’s sub-node coincidence was proposed in order to avoid the subjectivity of artificially determined weights and the inaccuracy of simple linear weighting in existing models.At last,a training test on the comprehensive similarity calculation model was performed,while the sample data were extracted from ontology-concept of variable evaluation indicators that come from command information systems established by different departments of combat forces.Experimental data show that compared with PSO-BP calculation model and principal-component linear weighted calculation model,the comprehensive similarity calculation model based on SA-BP algorithm achieves strong correlation,since its results and its Pearson correlation coefficient of the results evaluated by experts are increased by 0.0695 and 0.1351 respectively.The experimental results verify that,after training,SA-BP algorithm can converge better and achieve higher accurate when calculating ontology-concept similarity.Hence,key issues of integration for ontology-concept can be effectively solved.

Key words: BP neural network, Ontology integration, Semantic similarity calculation, Simulated annealing algorithm, Sub-nodecoincidence

CLC Number: 

  • TP391
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