Attention mechanism enables the Graph Neural Networks(GNNs) to learn the attention weights between the target node and its one-hop neighbors, the performance is further improved. However, the most existing GNNs are oriented to homogeneous graphs and each layer can only aggregate the information of ...
To this end, we propose a novel model HiAM (Hierarchical Attention based Model) for knowledge graph multi-hop reasoning. HiAM makes use of predecessor paths to provide more accurate semantics for entities and explores the effects of different granularities. Firstly, we extract predecessor paths of ...
论文解读:Improving the robustness of machine reading comprehension model with hierarchical knowledge and auxiliary unanswerability prediction 摘要: 先前深度学习方法在MRC任务上均成功应用,但他们普遍脆弱且在给定一些对抗噪声时不鲁棒。为了提升MRC,我们通过引入额... ...
Incorporating relation paths in neural relation extraction. Empirical Methods in Natural Language Processing. Copenhagen: ACL; 2017. p. 1768–77. 19. Zhang Y, Zheng W, Lin H, Wang J, Yang Z, Dumontier M. Drug-drug interaction extraction via hierarchical rnns on sequence and shortest ...
Type-adaptive graph Transformer for heterogeneous information networks Article 24 August 2024 A Deep Hybrid Pooling Architecture for Graph Classification with Hierarchical Attention Chapter © 2021 MG2Vec+: A multi-headed graph attention network for multigraph embedding Article 26 September 2022 1...
Multi-Hop Question Generation Using Hierarchical Encoding-Decoding and Context Switch Mechanism Neural auto-regressive sequence-to-sequence models have been dominant in text generation tasks, especially the question generation task. However, neural ge... T Ji,C Lyu,Z Cao,... - 《Entropy》 被引量...
Multi-Hop Question Generation Using Hierarchical Encoding-Decoding and Context Switch Mechanism Neural auto-regressive sequence-to-sequence models have been dominant in text generation tasks, especially the question generation task. However, neural ge... T Ji,C Lyu,Z Cao,... - 《Entropy》 被引量...
HiAM: A Hierarchical Attention based Model for knowledge graph multi-hop reasoning Learning to reason in large-scale knowledge graphs has attracted much attention from research communities recently. This paper targets a practical task of multi-hop reasoning in knowledge graphs, which can be applied in...
Incorporating relation paths in neural relation extraction. Empirical Methods in Natural Language Processing. Copenhagen: ACL; 2017. p. 1768–77. 19. Zhang Y, Zheng W, Lin H, Wang J, Yang Z, Dumontier M. Drug-drug interaction extraction via hierarchical rnns on sequence and shortest ...
2.3. Hyperbolic Neural Networks Hyperbolic space has always been a popular research domain in mathematics. Some works have been conducted to explore the treelike structure of graphs [34,35] and the relations between hyperbolic space and hierarchical data such as languages and complex networks [36,...