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A temporal interaction-enhanced multi-view framework for knowledge tracing via self-supervised contrastive learning

delete2026-01-20
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PRE
AI
L
Liqing Qiu *
Q
Qingyun Zhu
DOI：10.1016/j.knosys.2026.115332delete
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Abstract

Abstract

En 中文
• A joint modeling method integrates heterogeneous and interaction-directed graphs. • A self-supervised contrastive learning mechanism enhances multi-view graph embeddings. • Temporal information is incorporated to mitigate time decay effects in learning behavior.

Journal

K
Knowledge-Based Systems
IF:
7.6
Papers:
1.2W
Citations:
4.5W

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No organization information available