TaxoExpan

2000년 도입 · 논문 1편에서 사용

TaxoExpan 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.

출처: TaxoExpan: Self-supervised Taxonomy Expansion with Position-Enhanced Graph Neural Network

소개 논문: TaxoExpan: Self-supervised Taxonomy Expansion with Position-Enhanced Graph Neural Network