Papers with graph-based semi-supervised classification

1 papers
Fine-Grained Entity Typing via Hierarchical Multi Graph Convolutional Networks (D19-1)

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Challenge: Existing methods for inferring the fine-grained type of an entity from knowledge base are incomplete and lack type information.
Approach: They propose a novel Deep Learning architecture to infer the fine-grained type of an entity from a knowledge base.
Outcome: The proposed method significantly outperforms four state-of-the-art methods on two large-scale datasets.

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