基于自适应学习的知识本体推荐系统的研究与实现

Design And Implementation Of Ontology Recommendation System Based On Adaptive Learning

针对当前的在线教育系统不能根据学习者个人的资源偏好对合理地推荐学习资源的情况,本文提出基于自适应学习的知识本体推荐系统OALRS(theOntology-basedAdaptiveLearningRecommendation System)的实现架构。本文以小学数学知识为数据源,引入知识图谱与本体论知识,遵循教学进度合理地安排教学知识图,并将本体化的知识图合并为全局知识本体。最后,结合自适应学习策略,根据学习者当前的学习情况与学习偏好个性化地推荐学习资源。

Since most of existing education systems fail to recommend learning resources rationally according to the learner’s learning situation and preferences, the implementation framework of ontology recommendation system OALRS has been proposed in this paper. According to knowledge graph and ontology, this paper takes primary school mathematics knowledge as the data source, arranges the teaching knowledge maps reasonably according to the teaching progress, and merges the ontological knowledge maps into the global knowledge ontology. Combined the adaptive learning strategy, learning resources can be automatically recommended depending on the learner’s own situation and preference.