An Improved Algorithm For Conceptual Semantic Similarity In Domain Ontology

DOI

10.2991/jimec-17.2017.9How to use a DOI?

Keywords

domain ontology; semantic similarity; node density; semantic coincidence

Abstract

With the extensive application of ontology in many fields, the semantic similarity computation based on domain ontology has been a hot research topic. At present, taking advantage of the upper and lower layer structure of ontology to calculate the semantic similarity is the most common approach. But for these approaches, the analysis of selected factors is not comprehensive, and the result of single factor is not close to the overall semantic similarity value. In this paper, that the computing result of node density may be not in the range of meaningful value is improved, and the weight of each ancestor node is added on the basis of semantic coincidence. Considering the semantic distance, node depth, node density and semantic coincidence, an improved algorithm for conceptual semantic similarity in domain ontology is proposed. By comparing and analysing the results of the experiment, it shows that the improved algorithm has higher accuracy for the value of single factor and the overall semantic similarity.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yaya Zhen
AU  - Xian Zhong
AU  - Lin Li
AU  - Luo Zhong
PY  - 2017/10
DA  - 2017/10
TI  - An Improved Algorithm For Conceptual Semantic Similarity In Domain Ontology
BT  - Proceedings of the 2017 2nd Joint International Information Technology, Mechanical and Electronic Engineering Conference (JIMEC 2017)
PB  - Atlantis Press
SP  - 44
EP  - 48
SN  - 2352-538X
UR  - https://doi.org/10.2991/jimec-17.2017.9
DO  - 10.2991/jimec-17.2017.9
ID  - Zhen2017/10
ER  -