WebEvery Document Owns Its Structure: Inductive Text Classification via Graph Neural Networks . Text classification is fundamental in natural language processing (NLP), and Graph Neural Networks (GNN) are recently applied in this task. However, the existing graph-based works can neither capture the contextual word relationships within each ... WebApr 22, 2024 · We first build individual graphs for each document and then use GNN to learn the fine-grained word representations based on their local structure, which can …
Every Document Owns Its Structure: Inductive Text Classification via ...
WebFind and fix vulnerabilities Codespaces. Instant dev environments WebJun 22, 2024 · Zhang Y, Yu X, Cui Z, Wu S, Wen Z, Wang L (2024) Every document owns its structure: Inductive text classification via graph neural networks. In: Jurafsky D, Chai J, Schluter N, Tetreault JR (eds) Proceedings of the 58th annual meeting of the association for computational linguistics, ACL 2024, Online, July 5–10, 2024, Association for ... thomas fyson
Every Document Owns Its Structure: Inductive Text …
WebAug 18, 2024 · DBM is the basic modeling unit of network, and it is a model structure composed of RBM with undirected graph connection. The schematic diagram of DBM can be seen in Figure 1. It is mainly composed of unsupervised pretraining and supervised fine-tuning [ 11 ], which are roughly consistent with network results when selecting network … WebEvery Document Owns Its Structure: Inductive Text Classification via Graph Neural Networks . Text classification is fundamental in natural language processing (NLP), and … WebApr 25, 2024 · Xuan-Wei Wu, Lingxiao Zhao, and Leman Akoglu. 2024. A Quest for Structure: Jointly Learning the Graph Structure and Semi-Supervised Classification. ... Every Document Owns Its Structure: Inductive Text Classification via Graph Neural Networks. ArXiv abs/2004.13826(2024). Google Scholar; Yufeng Zhang, Jinghao Zhang, … ufton lane sittingbourne