Encoding Social Information with Graph Convolutional Networks for Political Perspective Detection in News Media Chang Li, Dan Goldwasser ACL 2019 Attention Guided Graph Convolutional Networks for Relation Extraction Zhijiang Guo, Yan Zhang, Wei Lu ACL 2019 Incorporating Syntactic and Semantic Information in...
Encoding Social Information with Graph Convolutional Networks forPolitical Perspective Detection in News Media Chang Li, Dan Goldwasser ACL 2019 A Neural Multi-digraph Model for Chinese NER with Gazetteers Ruixue Ding, Pengjun Xie, Xiaoyan Zhang, Wei Lu, Linlin Li, Luo Si ACL 2019 Tree Communic...
The widespread dissemination of fake news on social media has substantial economic and social implications. Although traditional propagation-based methods employing graph neural networks show promise for fake news detection, they disregard the influence of confirmation bias in the spread of fake news betwe...
Encoding Social Information with Graph Convolutional Networks for Political Perspective Detection in News Media. ACL 2019. paper Chang Li, Dan Goldwasser. Fine-grained Event Categorization with Heterogeneous Graph Convolutional Networks. IJCAI 2019. paper Hao Peng, Jianxin Li, Qiran Gong, Yangqiu Song...
The use of Graph Theory on social media data is a promising approach to identify emergent properties of the complex physical and cognitive interactions that occur between humans and nature. To test the effectivity of this approach at global scales, Insta
or gender bias. machine learning features developed using tigergraph can be used to explain clearly why the ai solution arrived at a particular decision based on the combination of the computed feature values. moreover, tigergraph’s graphstudio can show how the features were computed and what led...
Lafayette, Calif., November 13, 2024 – Franz Inc., an early innovator in Artificial Intelligence (AI) and leading provider of Graph Database technology for Neuro-Symbolic AI Solutions, today announced that it’s flagship platform, AllegroGraph, was voted the “Best Knowledge Graph” in the 20...
Entity alignment (EA) aims to automatically match entities in different knowledge graphs, which is beneficial to the development of knowledge-driven applications. Representation learning has powerful feature capture capability and it is widely used in the field of natural language processing. Compared wit...
Explanation-based Weakly-supervised Learning of Visual Relations with Graph Networks. Federico Baldassarre and Kevin Smith and Josephine Sullivan and Hossein Azizpour. ECCV 2020.paper GCAN: Graph-aware Co-Attention Networks for Explainable Fake News Detection on Social Media. Lu, Yi-...
Santos C N, Guimaraes V.Boosting named entity recognition with neural character embeddings. Proceedings of NEWS 2015 The Fifth Named Entities Workshop, 2015. Chiticariu L, Krishnamurthy R, Li Y, et al.Domain adaptation of rule-based annotators for named-entity recognition tasks. EMNLP2010: 1002...