Personalized Course Recommendation System Fusing with Knowledge Graph and Collaborative Filtering
Personalized courses recommendation technology is one of the hotspots in online education field. A good recommendation algorithm can stimulate learners' enthusiasm and give full play to different learners' learning personality. At present, the popular collaborative filtering algorithm igno...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8487836/ https://www.ncbi.nlm.nih.gov/pubmed/34616447 http://dx.doi.org/10.1155/2021/9590502 |
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author | Xu, Gongwen Jia, Guangyu Shi, Lin Zhang, Zhijun |
author_facet | Xu, Gongwen Jia, Guangyu Shi, Lin Zhang, Zhijun |
author_sort | Xu, Gongwen |
collection | PubMed |
description | Personalized courses recommendation technology is one of the hotspots in online education field. A good recommendation algorithm can stimulate learners' enthusiasm and give full play to different learners' learning personality. At present, the popular collaborative filtering algorithm ignores the semantic relationship between recommendation items, resulting in unsatisfactory recommendation results. In this paper, an algorithm combining knowledge graph and collaborative filtering is proposed. Firstly, the knowledge graph representation learning method is used to embed the semantic information of the items into a low-dimensional semantic space; then, the semantic similarity between the recommended items is calculated, and then, this item semantic information is fused into the collaborative filtering recommendation algorithm. This algorithm increases the performance of recommendation at the semantic level. The results show that the proposed algorithm can effectively recommend courses for learners and has higher values on precision, recall, and F1 than the traditional recommendation algorithm. |
format | Online Article Text |
id | pubmed-8487836 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-84878362021-10-05 Personalized Course Recommendation System Fusing with Knowledge Graph and Collaborative Filtering Xu, Gongwen Jia, Guangyu Shi, Lin Zhang, Zhijun Comput Intell Neurosci Research Article Personalized courses recommendation technology is one of the hotspots in online education field. A good recommendation algorithm can stimulate learners' enthusiasm and give full play to different learners' learning personality. At present, the popular collaborative filtering algorithm ignores the semantic relationship between recommendation items, resulting in unsatisfactory recommendation results. In this paper, an algorithm combining knowledge graph and collaborative filtering is proposed. Firstly, the knowledge graph representation learning method is used to embed the semantic information of the items into a low-dimensional semantic space; then, the semantic similarity between the recommended items is calculated, and then, this item semantic information is fused into the collaborative filtering recommendation algorithm. This algorithm increases the performance of recommendation at the semantic level. The results show that the proposed algorithm can effectively recommend courses for learners and has higher values on precision, recall, and F1 than the traditional recommendation algorithm. Hindawi 2021-09-25 /pmc/articles/PMC8487836/ /pubmed/34616447 http://dx.doi.org/10.1155/2021/9590502 Text en Copyright © 2021 Gongwen Xu et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Xu, Gongwen Jia, Guangyu Shi, Lin Zhang, Zhijun Personalized Course Recommendation System Fusing with Knowledge Graph and Collaborative Filtering |
title | Personalized Course Recommendation System Fusing with Knowledge Graph and Collaborative Filtering |
title_full | Personalized Course Recommendation System Fusing with Knowledge Graph and Collaborative Filtering |
title_fullStr | Personalized Course Recommendation System Fusing with Knowledge Graph and Collaborative Filtering |
title_full_unstemmed | Personalized Course Recommendation System Fusing with Knowledge Graph and Collaborative Filtering |
title_short | Personalized Course Recommendation System Fusing with Knowledge Graph and Collaborative Filtering |
title_sort | personalized course recommendation system fusing with knowledge graph and collaborative filtering |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8487836/ https://www.ncbi.nlm.nih.gov/pubmed/34616447 http://dx.doi.org/10.1155/2021/9590502 |
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