计算机应用与软件2026，Vol.43Issue(4)：232-239,262,9.DOI:10.3969/j.issn.1000-386x.2026.04.033
基于权重优化的遗忘门控深度注意力记忆知识追踪
FORGETTING GATED DEEP ATTENTION MEMORY KNOWLEDGE TRACKING BASED ON WEIGHT OPTIMIZATION
周巧英1
作者信息
- 1. 安阳职业技术学院 河南 安阳 455000
- 折叠
摘要
Abstract
In order to combine forgetting features with knowledge states and comprehensively analyze their joint effects on predicted answers,a knowledge tracking method based on forgetting gated deep attention memory is proposed.The weight optimization forgetting gating mechanism was incorporated into the attention memory structure,and the potential conceptual information proportion was adjusted by optimizing the weight to optimize the performance of information capture ability.Based on the constantly developing knowledge state of students,we captured embedded representations of potential concepts and their relationships from the dynamic potential concept map,and used their useful information to sort the problems.Experimental verification was conducted on four datasets,and the results demonstrated the superiority of the proposed method.关键词
注意力机制/权重优化/嵌入表示/遗忘门控Key words
Attention mechanism/Weight optimization/Embedded representation/Forgetting gate分类
信息技术与安全科学引用本文复制引用
周巧英..基于权重优化的遗忘门控深度注意力记忆知识追踪[J].计算机应用与软件,2026,43(4):232-239,262,9.
