Ontology similarity measuring and ontology mapping algorithm based on MEE criterion

被引：0

作者：

Gao, Wei ^{[1
]}

Xu, Tianwei ^{[1
]}

机构：

[1] Yunnan Normal University, School of Information Science and Technology, Kunming, China

来源：

Energy Education Science and Technology Part A: Energy Science and Research | 2014年 / 32卷 / 05期

关键词：

Conformal mapping - Entropy - Learning algorithms - Learning systems;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

The minimum error entropy (MEE) criterion has been raising large attention due to its promising perspectives for applications in machine learning and other specific engineering. In the context of ontology similarity measuring and ontology mapping, the learning algorithm is concerned with the estimation of an optimization ontology function based on various learning tricks, and the obtained ontology function maps each vertex on ontology graph into a real number. In this work, we raise new ontology similarity measuring and ontology mapping algorithm based on MEE criterion. Two experiments raised in our paper present the efficiency of the new algorithms. © Sila Science. All rights reserved.

引用

页码：3793 / 3806