The superiority of the proposed approach compared to the current state-of-the-art algorithms.

<p>The proposed strategy has demonstrated higher performance compared to other methods in terms of accuracy and AUC on three distinct datasets.</p>

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Ailian Gao (20629841) (author)
مؤلفون آخرون:	Zenglei Liu (20629838) (author)
منشور في:	2025
الموضوعات:	Cancer Science Policy Biological Sciences not elsewhere classified students &# 8217 integrate temporal information conducted comparison experiments bidirectional lstm model series forecasting pipeline machine learning algorithms proposed lstkt model proposed informer model publicly available dataset individual knowledge states informer </ p achieved promising outcomes short sequence prediction probability sparse self implement knowledge tracing long sequence time sparse self series prediction knowledge tracing sequence time tracing studies time stamps time stamp ednet dataset assistments2017 dataset assistments2009 dataset current knowledge target exercises previous approaches learning performance extensively utilized existing models exercising recordings decoder architecture canonical encoder attention module attention mechanism answering records 82 %. 81 %.
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