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Analysis and optimization of student learning paths based on CRNN and sequential data. [PDF]

PLoS One
Deng M, Lu L, Wen S.
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Intelligent deep learning model for recommending ideological and political music education resources. [PDF]

Sci Rep
Zhang L.
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Disentangled Relational Graph Neural Network with Contrastive Learning for Knowledge Graph Completion

Hong Yin, Jiang Zhong, Rongzhen Li, Xue Li   +3 more
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Editorial: Data science and machine learning for psychological research. [PDF]

Front Psychol
Yu CH.
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Symbolic rule-based knowledge graph completion

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XLNet For Knowledge Graph Completion

2021 2nd International Conference on Education, Knowledge and Information Management (ICEKIM), 2021
As the one of databases in artificial intelligence systems, knowledge graph has been widely used nowadays. Although the number of entities in current knowledge graphs has reached tens of millions or even billions level, directed cyclic graphs of their relations and entities composition were still relatively sparse.
Jie Liu, Xitong Ning, Wansong Zhang
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Knowledge Graph Completion via Complete Attention between Knowledge Graph and Entity Descriptions

Proceedings of the 3rd International Conference on Computer Science and Application Engineering, 2019
The objective of learning representation of knowledge graph is assumed to encode both entities and relations into a continuous low-dimensional vector space. Previous methods usually represent the same entity in different triples with the same representation.
Minjun Zhao, Yawei Zhao, Bing Xu
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MRGAT: Multi-Relational Graph Attention Network for knowledge graph completion

Neural Networks, 2022
One of the most effective ways to solve the problem of knowledge graph completion is embedding-based models. Graph neural networks (GNNs) are popular and promising embedding models which can exploit and use the structural information of neighbors in knowledge graphs.
Guoquan Dai, Xizhao Wang, Xiaoying Zou, Chao Liu, Si Cen   +4 more
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Multi-View Riemannian Manifolds Fusion Enhancement for Knowledge Graph Completion

IEEE Transactions on Knowledge and Data Engineering
As the application of knowledge graphs becomes increasingly widespread, the issue of knowledge graph incompleteness has garnered significant attention. As a classical type of non-euclidean spatial data, knowledge graphs possess various complex structural
Linyu Li, Zhi Jin, Xuan Zhang, Haoran Duan, Jishu Wang, Zhengwei Tao, Haiyan Zhao, Xiaofeng Zhu   +7 more
semanticscholar   +1 more source