期刊论文

Li, Q

英文

Expert Systems with Applications

0957-4174

2024

241

122451

10.1016/j.eswa.2023.122451

National Key R&D Program of China [2022ZD0117103]; National Natural Science Foundation of China [62293554, 62107017, 62207017]; China Postdoctoral Science Foundation, China [2020M682454, 2022M711282]; Higher Education Science Research Program of China Association of Higher Education [23XXK0301]; Hubei Provincial Natural Science Foundation of China [2022CFB414, 2023AFA020]; Knowledge Innovation Program of Wuhan-Shuguang Project, China [2022010801020287]; Fundamental Research Funds for the Central Universities, China [CCNU22LJ005, CCNU22XJ033]

本校为第一且通讯机构

Intelligent tutoring systems (ITS) have received much attention recently as online learning has taken off and is replacing offline instruction in many cases. It analyses user behavior and customizes personalized learning strategies for users through artificial intelligence technology. ITS encompasses a variety of entities and multiple relations, making it suitable to be represented as a graph. This perfectly aligns with the utilization of graph embedding (GE) for downstream ITS tasks. Existing GE methods cannot effectively model ITS data because the user evolution in ITS is discrete in time. T...