借助GA-KNN及线性规划的基于本体的教学资源分类方案的研究

Study on the Classification Scheme of Education Resources Based on Ontology via GA-KNN and Linear Programming

随着信息技术的高速发展,Internet上积累了大量的优秀的教学资源,人们开始利用网络这个学习平台来访问这些优秀资源,以达到自主学习的目的。为了能够快速访问到所需资源,必须对繁杂的资源进行分类。传统的人工分类难以完成这一工作,利用文本自动化分类技术,则可以实现对教学资源进行快速而有效的分类。本文将利用GA-KNN及线性规划来实现教育资源的自动化分类,从实验结果来看,它基本达到了预期的效果,大大提高了分类的精度。

With the rapid development of information technology, the Internet has accumulated a large number of outstanding teaching resources, and people begin to use the network learning platform to access these excellent resources in order to achieve the purpose of autonomous learning. In order to be able to quickly access to the required resources, we must classify multifarious resources. The traditional artificial classification is difficult to finish this job. Using text automatic classification technology, we can realize the rapid and effective classification of teaching resources. This article will use the GA-KNN and linear programming to achieve the automatic classification of education resources. From the experimental results, it achieves the expected effect, greatly improving the accuracy of classification.