Personalized Distance Learning System based on Sequence Analysis Algorithm

Ji-chun Zhao, Shi-hong Liu, Jun-feng Zhang


Personalized learning system can provide users with the most valuable learning resource to them through intelligent recommendation models and algorithms. This paper proposed the classical sequence analysis algorithms, and the Prefixspan algorithm is validated through distance learning platform data. In the event that the minimum support threshold is between 0.003 to 0.004%, test data shows that the performance of the algorithm's accuracy rate is relatively stable and the recommendation effect is satisfactory.


Distance Learning; Sequence Analysis; Personalized Learning

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International Journal of Online and Biomedical Engineering (iJOE) – eISSN: 2626-8493
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