Attention-based Multi-level Feature Fusion for Named Entity Recognition

IJCAI 2020, pp. 3594-3600, 2020.

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We propose a novel framework called attention-based multi-level feature fusion, which is used to capture the multi-level features from different perspectives to improve NER

Abstract:

Named entity recognition (NER) is a fundamental task in the natural language processing (NLP) area. Recently, representation learning methods (e.g., character embedding and word embedding) have achieved promising recognition results. However, existing models only consider partial features derived from words or characters while failing to ...More

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