Shun Mao
Biographic Data
| ID | 10054285 |
|---|---|
| NAME | Shun Mao |
| GIVEN NAMES | Shun |
| FAMILY NAME | Mao |
| SIGNATURE | MAO S |
| AFFILIATIONS | South China Normal University |
| ORCID | 0000-0001-6625-2348 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Modeling Periodic Learning and Forgetting Behaviors for Enhanced Knowledge Tracing
Knowledge tracing (KT) is a critical component of intelligent tutoring systems, which aim to track and predict students’ evolving knowledge states based on their interaction histories in online learning environments. However, most existing KT models fail to account for the periodic nature of student learning, in which knowledge acquisition occurs in concentrated study sessions, followed by periods of forgetting during breaks. To address this limi…
Modeling the Type Hierarchy in High-Dimensional Box Space for Fine-Grained Entity Typing
A critical component of fine-grained entity typing is the existence of precise relationship between entity types, such as type hierarchy. Previous approaches for fine-grained entity typing typically model the type hierarchy in vector space, which causes it extremely hard to precisely capture the complex relationship between entity types. To overcome the challenge of modeling type hierarchy in vector space, this article proposes for the first time…
Knowledge-Associated Embedding for Memory-Aware Knowledge Tracing
Knowledge tracing (KT) refers to predicting learners’ performance in the future according to their historical learning interactions, which has become an essential task for the computer-aided education (CAE) system. Recent studies alleviate the data sparsity problem by mining higher-order information between questions and skills. However, the effect of multiple skills in the question is not distinguished, and various learning behaviors need to be …
No prominent works on this page.
Knowledge-Associated Embedding for Memory-Aware Knowledge Tracing
Knowledge tracing (KT) refers to predicting learners’ performance in the future according to their historical learning interactions, which has become an essential task for the computer-aided education (CAE) system. Recent studies alleviate the data sparsity problem by mining higher-order information between questions and skills. However, the effect of multiple skills in the question is not distinguished, and various learning behaviors need to be …
Modeling the Type Hierarchy in High-Dimensional Box Space for Fine-Grained Entity Typing
A critical component of fine-grained entity typing is the existence of precise relationship between entity types, such as type hierarchy. Previous approaches for fine-grained entity typing typically model the type hierarchy in vector space, which causes it extremely hard to precisely capture the complex relationship between entity types. To overcome the challenge of modeling type hierarchy in vector space, this article proposes for the first time…
Modeling Periodic Learning and Forgetting Behaviors for Enhanced Knowledge Tracing
Knowledge tracing (KT) is a critical component of intelligent tutoring systems, which aim to track and predict students’ evolving knowledge states based on their interaction histories in online learning environments. However, most existing KT models fail to account for the periodic nature of student learning, in which knowledge acquisition occurs in concentrated study sessions, followed by periods of forgetting during breaks. To address this limi…
Computer Science (2 works) · Forgetting (2 works) · Intelligent Tutoring Systems and Adaptive Learning (2 works) · Tracing (2 works) · Advanced Database Systems and Queries (1 works) · Advanced Graph Neural Networks (1 works) · Artificial Intelligence (1 works) · Artificial neural network (1 works) · Cognitive psychology (1 works) · Distributed and Parallel Computing Systems (1 works)