是为序 论文名:Dependency-driven Relation Extraction with Attentive Graph Convolutional Networks 论文链接: ACL2021 的 long paper,能中长文,必有可取之处。 Motivation:很多论文使用 句法依存树 来辅助抽取一句话中的两个entity的关系,这些句法依存树多半是使用自动的工具来抽取的,自然具有很多不必要的信息或者错误...
[论文阅读]Dependency-driven Relation Extraction with Attentive Graph Convolutional Networks[ACL2021] 论文地址:https://aclanthology.org/2021.acl-long.344/ 代码地址:https://github.com/cuhksz-nlp/RE-AGCN 依赖关系标注工具:https://stanfordnlp.github.io/CoreNLP/ ACE2005处理参考:https://github.com/...
CONVOLUTIONAL neural networksDEEP learningSENTIMENT analysisSOCIAL mediaBackground and Objectives: Twitter is a microblogging platform for expressing assessments, opinions, and sentiments on different topics and events. While there have been several studies around sentiment analysis of...
Graph Convolutional Networks (GCN)(图卷积网络) 3,网络架构(DAGL) 文章提出一种交替级联的图像重建网络,由多个特征提取模块和基于动态图的多头信息聚合模块组成,结构如下图所示: 提出的模型DAGL的概述如图1所示,主要由两个部分组成:特征提取模块(FEM)和基于图的多头特征聚合模块(M-GFAM)。 与许多图像恢复网络类...
In this paper, we propose attentive Knowledge-aware Graph convolutional networks with Collaborative Guidance for personalized Recommendation (CG-KGR). CG-KGR is a novel knowledge-aware recommendation model that enables ample and coherent learning of KGs and user-item interactions, via our proposed ...
Multi-Agent Deep Reinforcement Learning using Attentive Graph Neural Architectures for Real-Time Strategy GamesPerformance evaluation WJ Yun,S Yi,J Kim 被引量: 0发表: 2021年 Attentive Multi-Task Deep Reinforcement Learning Sharing knowledge between tasks is vital for efficient learning in a multi-task...
Ronneberger, O., Fischer, P., Brox, T.: U-net: Convolutional networks for biomedical image segmentation. In: MICCAI, (2015) Nirkin, Y., Wolf, L., Hassner, T.: Hyperseg: Patch-wise hypernetwork for real-time semantic segmentation. In: CVPR, (2021) Li, X., You, A., Zhu, Z....
IntagHand [23] directly regresses a fixed number of mesh vertex coordinates using a graph convolutional net- work (GCN). These methods mainly model the shape of two interacting hands based on a low-resolution mesh represen- tation with a fixed topology of...
[33] introduce neural tensor networks for knowledge graph embedding, which allows mediated interaction of entity embeddings via a tensor. Schlichtkrull et al. [31] present relational graph convolutional networks for knowledge graph completion. Shi and Weninger [32] present a shared variable neural ...
Recently, graph neural networks for semi-supervised classification have been widely studied. However, existing methods only use the information of limited neighbors and do not deal with the inter-class connections in graphs. In this paper, we propose Adaptive aggregation with Class-Attentive Diffusion...