International Journal of Chemical and Biomolecular Science
Articles Information
International Journal of Chemical and Biomolecular Science, Vol.1, No.3, Oct. 2015, Pub. Date: Sep. 1, 2015
Ontology Similarity Measuring and Ontology Mapping Algorithms Via Graph Semi-Supervised Learning
Pages: 179-184 Views: 3584 Downloads: 907
[01] Yun Gao, Department of Editorial, Yunnan Normal University, Kunming, China.
[02] Li Liang, School of Information Science and Technology, Yunnan Normal University, Kunming, China.
[03] Wei Gao, School of Information Science and Technology, Yunnan Normal University, Kunming, China.
Ontology similarity calculation is important research topics in information retrieval and widely used in biology and chemical. By analyzing the technology of semi-supervised learning, we propose the new algorithm for ontology similarity measure and ontology mapping. The ontology function is obtained by learning the ontology sample data which is consisting of labeled and unlabeled ontology data. Via the ontology semi-supervised learning, the ontology graph is mapped into a line consists of real numbers. The similarity between two concepts then can be measured by comparing the difference between their corresponding real numbers. The experiment results show that the proposed new algorithm has high accuracy and efficiency on ontology similarity calculation and ontology mapping.
Ontology, Similarity Measure, Ontology Mapping, Semi-Supervised Learning
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