Title: Similarity matrix learning for ontology application

Authors: Jianzhang Wu; Xiao Yu; Wei Gao

Addresses: School of Computer Science and Engineering, Southeast University, Nanjing 210096, China ' School of Continuing Education, Southeast University, Nanjing 210096, China ' School of Information Science and Technology, Yunnan Normal University, Kunming 650500, China

Abstract: In information retrieval, ontology is used to search the information which has highly semantic similarity of the original query concept, and return the results to the user. Ontology mapping is used to create the relationship between different ontologies, and the essence of which is similarity computation. In this article, we present new algorithms for ontology similarity measure and ontology mapping by determining the similarity matrix of ontology. The optimisation strategy and iterative procedure are designed in terms of metric distance learning tricks. The simulation experimental results show that the proposed new algorithms have high accuracy and efficiency on ontology similarity measure and ontology mapping in biology, physics applications, plant science and humanoid robotics.

Keywords: knowledge representation; ontology applications; similarity measures; ontology mapping; similarity matrix learning; ontologies; simulation.

DOI: 10.1504/IJITM.2016.073910

International Journal of Information Technology and Management, 2016 Vol.15 No.1, pp.1 - 13

Received: 09 May 2014
Accepted: 18 Oct 2014

Published online: 30 Dec 2015 *

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