Ontology Algorithm Based on Semi-supervised Eigenmap Learning

Authors

Bo Peng, School of Information Science and Technology, Yunnan Normal University, Kumming 650500, ChinaFollow
Tian-wei Xu, School of Information Science and Technology, Yunnan Normal University, Kumming 650500, ChinaFollow
Zhen Li, School of Information Science and Technology, Yunnan Normal University, Kumming 650500, ChinaFollow
Wei Gao, School of Information Science and Technology, Yunnan Normal University, Kumming 650500, ChinaFollow

Abstract

Ontology similarity calculation is an important research topic in information retrieval and it is also widely used in computer science. In this paper，we propose new algorithms for ontology similarity measurement and ontology mapping using Semi-supervised Eigenmap Learning method. Via the learning algorithm，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. Two experimental results show that the proposed new algorithm has high accuracy and efficiency on ontology similarity calculation and ontology mapping.

Recommended Citation

Peng, Bo; Xu, Tian-wei; Li, Zhen; and Gao, Wei (2013) "Ontology Algorithm Based on Semi-supervised Eigenmap Learning," Information Sciences Letters: Vol. 2 : Iss. 2 , PP -.
Available at: https://digitalcommons.aaru.edu.jo/isl/vol2/iss2/6