natural-language-processing-6
Taxonomy Expansion
3260 papers • 126 benchmarks • 313 datasets
Expand a seed taxonomy with new unseen node
(Image credit: Papersgraph)
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Most implemented papers
TaxoExpan: Self-supervised Taxonomy Expansion with Position-Enhanced Graph Neural Network
Jiawei Han, Zhihong Shen, Kuansan Wang, Chenyan Xiong, Jiaming Shen•Sat Jan 25 2020
A novel self-supervised framework, named TaxoExpan, which automatically generates a set of ⟨query concept, anchor concept⟩ pairs from the existing taxonomy as training data, and develops two innovative techniques, including a position-enhanced graph neural network that encodes the local structure of an anchor concept in theexisting taxonomy and a noise-robust training objective that enables the learned model to be insensitive to the label noise in the self- supervision data.