Abstract
The course recommendation algorithm fails to consider the impact of semantic correlation between course keywords on feature similarity calculation when modeling, resulting in low recommendation accuracy. An economic management course recommendation algorithm in intelligent education cloud platform is proposed. The text of economic management course is collected by web crawler technology, and the words are extracted by text word segmentation, removal of stop words and other preprocessing. Based on the word2vec model, the text word vector of economic management course is established to measure the similarity between words. The word vector clustering and TF-IDF word weight are used to represent the course features. Design the course recommendation algorithm, calculate the similarity between courses, and generate the course similarity matrix for course recommendation. The experimental results show that the recommendation accuracy of the economic management course recommendation algorithm designed in this paper is higher than 0.9% in the three aspects of course name, course overview and course objectives, and the maximum recommendation time is 5min, which has a good application effect.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Yang, Y., Zhong, Y., Li, J.: Intelligent information recommendation model construction simulation based on knowledge graph. Computer Simulation 38(1), 437-440, 480 (2021)
Wu, H., Xu, X., Meng, F.: Knowledge graph-assisted multi-task feature-based course recommendation algorithm. Comp. Eng. Appl. 57(21), 132-139 (2021)
Wang, S., Wu, Z.: Recommendation model using LSTM network and course association classification. J. Frontiers of Comp. Sci. Technol. 13(8), 1380-1389 (2019)
Zeng, X., Yang, Y., Wang, S., et al.: Hybrid recommendation algorithm based on deep learning. Computer Science 46(1), 126-130 (2019)
Shao, M., Zhang, S.: Hybrid information recommendation based on personalized adaptive learning. Computer Simulation 38(4), 408-411, 426 (2021)
Liu, L.: Top-N recommendation algorithm based on user diversity preference. Comp. Eng. Appl. 57(17), 116-121 (2021)
Li, X., Liu, H., Shi, H., et al.: Deep learning based course recommendation model. Journal of Zhejiang University(Engineering Science) 53(11), 2139-2145, 2162 (2019)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Wang, J. (2022). Economic Management Course Recommendation Algorithm in Smart Education Cloud Platform. In: Fu, W., Sun, G. (eds) e-Learning, e-Education, and Online Training. eLEOT 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 454. Springer, Cham. https://doi.org/10.1007/978-3-031-21164-5_6
Download citation
DOI: https://doi.org/10.1007/978-3-031-21164-5_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-21163-8
Online ISBN: 978-3-031-21164-5
eBook Packages: Computer ScienceComputer Science (R0)