计算机应用与软件2025，Vol.42Issue(5)：30-35,87,7.DOI:10.3969/j.issn.1000-386x.2025.05.005
基于网络表示学习算法的知识追踪模型
KNOWLEDGE TRACKING MODEL BASED ON NETWORK REPRESENTATION LEARNING ALGORITHM
摘要
Abstract
Aimed at the problem that the difficulty of exercises is not considered in the knowledge tracking model with consistent learning process,a method of quantifying the difficulty based on the results of weighted average answer time and error rate was proposed.Aimed at the problem that the knowledge concepts in the knowledge tracking model with consistent learning process were independent from each other,a network structure was proposed to represent the knowledge concepts.The first-order similarity and second-order similarity between the knowledge concept nodes were calculated based on the joint probability and empirical distribution.The LINE algorithm in the network embedding could retain the advantages of the network structure information.The knowledge concept represented by the network structure was embedded into the low dimensional feature vector.The effectiveness of the method is verified by establishing a model on real and public data.关键词
知识概念/问题难度/一阶相似性/二阶相似性/LINE算法/网络表示学习Key words
Knowledge concept/Problem difficulty/First-order similarity/Second-order similarity/LINE algorithm/Network representation learning分类
信息技术与安全科学引用本文复制引用
陈倩倩..基于网络表示学习算法的知识追踪模型[J].计算机应用与软件,2025,42(5):30-35,87,7.基金项目
中央高校基本科研业务费国家项目培育基金项目(N2123023). （N2123023）
