但是以往的研究忽略了一些问题:1,忽略了多模态信息以及高阶互补信息;2,忽略了文本内容的完整层次语意。该文章提出了一种 hierarchical multi-modal contextual attention network (HMCAN)用于多模态虚假新闻检测,可以建模多模态信息同时建模多层次语意关系。 具体来说,我们使用BERT和ResNet分别学习更好的文本和图像表示。
These features are adapted in Hierarchical Attention Network (HAN) to categorize sentiment grade. The training of HAN is performed using the proposed Competitive Swarm Water Wave Optimization (CSWWO) algorithm. The developed CSWWO algorithm is newly designed by integrating the Competitive Swarm ...
we propose to enhance the DST through employing a contextual hierarchical attention network to not only discern relevant information at both word level and turn level but also learn contextual representations. We further propose an adaptive objective to alleviate the slot imbalance problem by dynamically...
To overcome these limitations, this paper proposes a novel hierarchical multi-modal contextual attention network (HMCAN) for fake news detection by jointly modeling the multi-modal context information and the hierarchical semantics of text in a unified deep model. Specifically, we employ BERT and ...
Accurate and Explainable Recommendation via Hierarchical Attention Network Oriented Towards Crowd Intelligence Chao Yang,Weixin Zhou,Zhiyu Wang,... - Knowledge-Based S... - 2021 - 被引量: 0 Modeling Users' Behavior Sequences with Hierarchical Explainable Network for Cross-domain Fraud Detection Yongchu...
Paper tables with annotated results for A Hierarchical Attention Model for Social Contextual Image Recommendation
前者利用attention机制通过检索全局记忆去匹配上下文线索,来模仿人类的直观检索过程。后者采取LSTM网络学习内在逻辑顺序,通过保留和更新动态工作记忆,来整合上下文线索。这模仿了人类的推理过程。它比较慢但是有人类独特的推理力。(Baddeley, 1992[19:1])最后,根据上述情景层面和说话人层面的上下文线索,使用...
To address this problem, a global contextual residual convolutional neural network is proposed. The major novelties fall into three aspects. First, to make full use of the features from all intermediate layers and explore multiscale information, a new hierarchical structure is adopted in the CNN ...
The ambition of MGCF is to preserve the multilevel global context features from different hierarchical layers of DLCN. Unlike others by simply concatenating these features, we introduce the information entropy as an attention strategy to enhance useful global context cues. Moreover, considering the ...
attention based feature maps that highlights the semantic details inIby exploiting channel as well spatial attention. In order to extract the contextual spatial relationship between the objects inI, the feature map of levelL4of WCNN,F4, is given to the CSE network as shown in Fig.1. The ...