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Better Word Representations with Recursive Neural Networks for Morphology

Thang Luong,R. Socher,Christopher D. Manning

2013 · DBLP: conf/conll/LuongSM13
Conference on Computational Natural Language Learning · 910 Citations

TLDR

This paper combines recursive neural networks, where each morpheme is a basic unit, with neural language models to consider contextual information in learning morphologicallyaware word representations and proposes a novel model capable of building representations for morphologically complex words from their morphemes.