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    人工智能支持下教育知识图谱模型构建研究

    Research on Constructing Model of Educational Knowledge Map Supported by Artificial Intelligence

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【作      者】:

钟 卓, 唐烨伟, 钟绍春, 赵一婷


【关 键 词 】:

人工智能; 知识图谱; 模型构建; 机器学习; 学习路径; 自适应学习


【栏      目】:

学习环境与资源


【中文摘要】:

领域模型作为构建自适应学习系统的核心组件,引起了研究者的广泛关注。文章针对现有教育领域模型知识内容分散、能力刻画不足的问题,提出了能够建立知识、问题、能力三者间映射关系的教育知识图谱KQA模型。该模型由知识图式、问题图式、能力图式三层图式和知识内容、关联关系、映射关系、学习路径四个要素组成。利用基于机器学习的实体抽取、关系抽取、实体对齐等方法,从数据获取、知识抽取、知识融合、知识推理四个方面,提出了教育知识图谱KQA模型的构建方法。研究为知识图谱在教育领域的应用提供依据,对个性化学习的开展具有重要意义。


【英文摘要】:

As a core component of constructing adaptive learning system, domain model has attracted wide attention of researchers. In order to solve the problem of scattered knowledge content and insufficient ability description in existing educational domain models, this paper proposes a KQA model of educational knowledge map which can establish the mapping relationship among knowledge, problem and ability. This model consists of three schema of knowledge schema, problem schema and ability schema and four elements of knowledge content, association relationship, mapping relationship and learning path. Using the methods of entity extraction, relation extraction and entity alignment based on machine learning, this paper proposes the construction method of KQA model of educational knowledge map from four aspects: data acquisition, knowledge extraction, knowledge fusion and knowledge reasoning. This study provides a basis for the application of knowledge map in the field of education and is of great significance for the development of personalized learning.

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