郑州大学学报（理学版）2025，Vol.57Issue(3)：35-41,48,8.DOI:10.13705/j.issn.1671-6841.2023115
长尾分布下基于层内相似关系的认知诊断模型
Cognitive Diagnosis Model Based on Intra-layer Similarity with Long Tail Distribution
摘要
Abstract
Most of current cognitive diagnostic models that existed in the past predominantly relied on a-bundant student response records for diagnosis.However,in reality,the interconnections among students'response records,items,and knowledge concepts exhibited a long-tail distribution.That meant that some students had a limited number of response records,and some items were covered by only a few knowledge concepts.This challenge was posed for model training.To address this issue,a cognitive diag-nostic model based on intra-layer similarity relationships was proposed.Using a simple matching coeffi-cient,the similarity coefficients of students,items,and knowledge concepts were calculated based on their response records.This process established intra-layer similarity relationships for students,items,and knowledge concepts.These intra-layer relationships were then utilized by the model,and a relational graph convolutional network was employed to propagate information from head nodes to tail nodes.This approach aimed to improve the sparsity of inter-layer relationships in the tail nodes.A diagnostic function that incorporated knowledge point representations was used for cognitive diagnosis.关键词
认知诊断/长尾分布/相似性/层内相似关系/图卷积网络Key words
cognitive diagnosis/long-tailed distribution/similarity/intra-layer relationships/graph convolutional networks分类
计算机与自动化引用本文复制引用
王冕,张玉红,刘菲,卜晨阳,胡学钢..长尾分布下基于层内相似关系的认知诊断模型[J].郑州大学学报（理学版）,2025,57(3):35-41,48,8.基金项目
国家自然科学基金项目(61976077,62076085) （61976077,62076085）
安徽省自然科学基金项目(2208085MF170) （2208085MF170）
安徽省高校协同创新项目(GXXT-2022-040) （GXXT-2022-040）
