Multi-hop neighbor fusion enhanced hierarchical transformer for multi-modal knowledge graph completion Multi-modal knowledge graph (MKG) refers to a structured semantic network that accurately represents the real-world information by incorporating multiple m... Y Wang,B Ning,X Wang,... - 《World Wi...
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 ...
P Jansen - Twelfth Workshop on Graph-based Methods for Natural Language Processing 被引量: 1发表: 2018年 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, especi...
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 ...
Multi-hop hierarchical graph neural networks. In Proceedings of the 2020 IEEE International Conference on Big Data and Smart Computing (BigComp), Busan, Republic of Korea, 19–22 February 2020; pp. 82–89. [Google Scholar] Yang, Y.; Tang, X.; Zhang, X.; Ma, J.; Liu, F.; Jia, X...
The method uses a graph attention network [30] to calculate the weight of neighbors based on different order graphs. Additionally, it applies an attention mechanism to aggregate multi-order representations of nodes. Lv et al. [31] propose a novel framework called hierarchical graph enhanced event...
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,...