F-Score Driven Max Margin Neural Network for Named Entity Recognition in Chinese Social Media

EACL, pp. 713-718, 2017.

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To shrink the gap between label accuracy and F-Score, we propose a method to directly train on F-Score rather than label accuracy in our model

Abstract:

We focus on named entity recognition (NER) for Chinese social media. With massive unlabeled text and quite limited labelled corpus, we propose a semi-supervised learning model based on B-LSTM neural network. To take advantage of traditional methods in NER such as CRF, we combine transition probability with deep learning in our model. To b...More

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