A Vocabulary Recommendation System based on Knowledge Graph for Chinese Language Learning

Abstract

In order to solve the problem of vocabulary learning confusion of primary Chinese language learners as well as effectively meet the current situation of learning resources overload, this study constructs a Chinese vocabulary learning resources recommendation system based on knowledge graph. First of all, the research on computer-supported vocabulary learning and learning resources recommendation based on knowledge graph is systematically reviewed. Secondly, this study designs the learning resources and 10 kinds of relations of Hanyu Shuiping Kaoshi (HSK) three-level vocabulary, and gives symmetry or transitivity to each relation, creates learning resources ontology, and constructs learning resources recommendation system based on knowledge graph by using Protege, Apache Jena and Python, namely CiHai. Finally, through the trial of primary Chinese language learners, the semi-structured interview is used to evaluate the results. The results showed that learners are satisfied with the learning experience of the vocabulary recommendation system. CiHai is helpful in improving the learning effect of Chinese vocabulary.