面向中小学教育的知识图谱自动构建系统

Penghe Chen, Yu Lu, V. Zheng, Xiyang Chen, Xiaoqing Li
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引用次数: 23

摘要

基于知识图谱教育应用的迫切需求,我们开发了K12EduKG系统,用于K-12教育学科知识图谱的自动构建。K12EduKG利用异构领域特定的教育数据,提取教育概念并识别具有高教育意义的隐含关系。具体来说,对课程标准等教育数据采用命名实体识别(NER)技术提取教育概念,并利用数据挖掘技术识别教育概念之间的认知前提关系。在本文中,我们介绍了K12EduKG的细节,并用一个为数学主题构建的知识图来演示它。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An automatic knowledge graph construction system for K-12 education
Motivated by the pressing need of educational applications with knowledge graph, we develop a system, called K12EduKG, to automatically construct knowledge graphs for K-12 educational subjects. Leveraging on heterogeneous domain-specific educational data, K12EduKG extracts educational concepts and identifies implicit relations with high educational significance. More specifically, it adopts named entity recognition (NER) techniques on educational data like curriculum standards to extract educational concepts, and employs data mining techniques to identify the cognitive prerequisite relations between educational concepts. In this paper, we present details of K12EduKG and demonstrate it with a knowledge graph constructed for the subject of mathematics.
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