2019

Large-Scale Multi-Label Text Classification on EU Legislation

Chalkidis, Ilias, Fergadiotis, Manos, Malakasiotis, Prodromos et al.

Understand

We consider Large-Scale Multi-Label Text Classification (LMTC) in the legal domain.

We release a new dataset of 57k legislative documents from EURLEX, annotated with ~4.3k EUROVOC labels, which is suitable for LMTC, few- and zero-shot learning.
Experimenting with several neural classifiers, we show that BIGRUs with label-wise attention perform better than other current state of the art methods.
Domain-specific WORD2VEC and context-sensitive ELMO embeddings further improve performance.

Built on

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