Research on course recommendation technology based on behavior log of online education platform

Hui Li

doi:10.1117/12.2692450

23 August 2023 Research on course recommendation technology based on behavior log of online education platform

Hui Li

Proceedings Volume 12784, Second International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2023); 127842M (2023) https://doi.org/10.1117/12.2692450
Event: 2023 2nd International Conference on Applied Statistics, Computational Mathematics and Software Engineering (ASCMSE 2023), 2023, Kaifeng, China

Abstract

To address the user cold start problem of behavior log recommendation algorithm, Focor course recommendation algorithm based on course selection probability calculation is proposed. Focor uses genetic algorithm to filter the optimal feature subset from the feature set composed of course selection dataset, and uses LightGBM to train a binary classification model on the optimal feature subset for whether to select a course or not, and makes course recommendation based on the course selection probability output from the model. The course recommendation is based on the probability of course selection output from the model. The experimental results show that the proposed algorithm, Focor course recommendation algorithm, is compared with LightGBM, XGBoost, decision tree, random forest, logistic regression and other algorithms on real data sets for experiments and performance evaluation, and achieves better performance in terms of F1 scores.

Citation Download Citation

Hui Li "Research on course recommendation technology based on behavior log of online education platform", Proc. SPIE 12784, Second International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2023), 127842M (23 August 2023); https://doi.org/10.1117/12.2692450

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