Graph Models
TaxoExpan
Introduced by Shen et al. in TaxoExpan: Self-supervised Taxonomy Expansion with Position-Enhanced Graph Neural NetworkTaxoExpan is a self-supervised taxonomy expansion framework. It automatically generates a set of <query concept, anchor concept> pairs from the existing taxonomy as training data. Using such self-supervision data, TaxoExpan learns a model to predict whether a query concept is the direct hyponym of an anchor concept. TaxoExpan features: (1) a position-enhanced graph neural network that encodes the local structure of an anchor concept in the existing taxonomy, and (2) a noise-robust training objective that enables the learned model to be insensitive to the label noise in the self-supervision data.
Source: TaxoExpan: Self-supervised Taxonomy Expansion with Position-Enhanced Graph Neural Network
Papers
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