Course Recommendations in Online Education Based on Collaborative Filtering Recommendation Algorithm
In this paper, a personalized online education platform based on a collaborative filtering algorithm is designed by applying the recommendation algorithm in the recommendation system to the online education platform using a cross-platform compatible HTML5 and high-performance framework hybrid progra...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/6619249 |
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| _version_ | 1832550099649036288 |
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| author | Jing Li Zhou Ye |
| author_facet | Jing Li Zhou Ye |
| author_sort | Jing Li |
| collection | DOAJ |
| description | In this paper, a personalized online education platform based on a collaborative filtering algorithm is designed by applying the recommendation algorithm in the recommendation system to the online education platform using a cross-platform compatible HTML5 and high-performance framework hybrid programming approach. The server-side development adopts a mature B/S architecture and the popular development model, while the mobile terminal uses HTML5 and framework to implement the function of recommending personalized courses for users using collaborative filtering and recommendation algorithms. By improving the traditional recommendation algorithm based on collaborative filtering, the course recommendation results are more in line with users' interests, which greatly improves the accuracy and efficiency of the recommendation. On this basis, online teaching on this platform is divided into two modes: one mode is the original teacher uploads recorded teaching videos and students can learn by purchasing online or offline download; the other mode is interactive online live teaching. Each course is a separate online classroom; the teacher will publish online class information in advance, and students can purchase to get classroom number and password information online. |
| format | Article |
| id | doaj-art-c3fd4105fc514ea198eaae2eb6b2b8c3 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-c3fd4105fc514ea198eaae2eb6b2b8c32025-02-03T06:07:41ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/66192496619249Course Recommendations in Online Education Based on Collaborative Filtering Recommendation AlgorithmJing Li0Zhou Ye1Laboratory Center of Economics and Management, Zhejiang University of Finance and Economics, Hangzhou, Zhejiang 310018, ChinaOffice of Academic Affairs, Zhejiang University of Finance and Economics, Hangzhou, Zhejiang 310018, ChinaIn this paper, a personalized online education platform based on a collaborative filtering algorithm is designed by applying the recommendation algorithm in the recommendation system to the online education platform using a cross-platform compatible HTML5 and high-performance framework hybrid programming approach. The server-side development adopts a mature B/S architecture and the popular development model, while the mobile terminal uses HTML5 and framework to implement the function of recommending personalized courses for users using collaborative filtering and recommendation algorithms. By improving the traditional recommendation algorithm based on collaborative filtering, the course recommendation results are more in line with users' interests, which greatly improves the accuracy and efficiency of the recommendation. On this basis, online teaching on this platform is divided into two modes: one mode is the original teacher uploads recorded teaching videos and students can learn by purchasing online or offline download; the other mode is interactive online live teaching. Each course is a separate online classroom; the teacher will publish online class information in advance, and students can purchase to get classroom number and password information online.http://dx.doi.org/10.1155/2020/6619249 |
| spellingShingle | Jing Li Zhou Ye Course Recommendations in Online Education Based on Collaborative Filtering Recommendation Algorithm Complexity |
| title | Course Recommendations in Online Education Based on Collaborative Filtering Recommendation Algorithm |
| title_full | Course Recommendations in Online Education Based on Collaborative Filtering Recommendation Algorithm |
| title_fullStr | Course Recommendations in Online Education Based on Collaborative Filtering Recommendation Algorithm |
| title_full_unstemmed | Course Recommendations in Online Education Based on Collaborative Filtering Recommendation Algorithm |
| title_short | Course Recommendations in Online Education Based on Collaborative Filtering Recommendation Algorithm |
| title_sort | course recommendations in online education based on collaborative filtering recommendation algorithm |
| url | http://dx.doi.org/10.1155/2020/6619249 |
| work_keys_str_mv | AT jingli courserecommendationsinonlineeducationbasedoncollaborativefilteringrecommendationalgorithm AT zhouye courserecommendationsinonlineeducationbasedoncollaborativefilteringrecommendationalgorithm |