Knowledge Commons of Institute of Automation,CAS
Symbolic Knowledge Reasoning on Hyper-Relational Knowledge Graphs | |
Zikang Wang![]() ![]() ![]() | |
发表期刊 | IEEE Transactions on Big Data
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2024 | |
页码 | accept |
摘要 | Knowledge reasoning has been widely researched in knowledge graphs (KGs), but there has been relatively less research on hyper-relational KGs, which also plays an important role in downstream tasks. Existing reasoning methods on hyper-relational KGs are based on representation learning. Though this approach is effective, it lacks interpretability and ignores the graph structure information. In this paper, we make the first attempt at symbolic reasoning on hyper-relational KGs. We introduce rule extraction methods based on both individual facts and paths, and propose a rule-based symbolic reasoning approach, HyperPath. This approach is simple and interpretable, it can serve as a baseline model for symbolic reasoning in hyper-relational KGs. We provide experimental results on almost all datasets, including five large-scale datasets and seven sub-datasets of them. Experiments show that the expressive power of the proposed model is similar to simple neural networks like convolutional networks, but not as advanced as more complex networks such as Transformer and graph convolutional networks, which is consistent with the performance of symbolic methods on KGs. Furthermore, we also analyze the impact of rule length and hyperparameters on the model's performance, which can provide insights for future research in hypergraph symbolic reasoning. The code is available at https://github.com/von1000/HyperPath. |
关键词 | hyper-relational knowledge graph, knowledge reasoning, multi-hop reasoning |
收录类别 | SCI |
七大方向——子方向分类 | 知识表示与推理 |
国重实验室规划方向分类 | 复杂系统建模与推演 |
是否有论文关联数据集需要存交 | 否 |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/57437 |
专题 | 舆论大数据科学与技术应用联合实验室 |
通讯作者 | Zikang Wang |
作者单位 | Institute of Automation, Chinese Academy of Sciences |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Zikang Wang,Linjing Li,Daniel Zeng. Symbolic Knowledge Reasoning on Hyper-Relational Knowledge Graphs[J]. IEEE Transactions on Big Data,2024:accept. |
APA | Zikang Wang,Linjing Li,&Daniel Zeng.(2024).Symbolic Knowledge Reasoning on Hyper-Relational Knowledge Graphs.IEEE Transactions on Big Data,accept. |
MLA | Zikang Wang,et al."Symbolic Knowledge Reasoning on Hyper-Relational Knowledge Graphs".IEEE Transactions on Big Data (2024):accept. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
paper.pdf(4767KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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