Named entity recognition for Chinese microblog with convolutional neural network

L. Zhang, Huan Zhao
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引用次数: 2

Abstract

Named Entity Recognition (NER) has usually focused on traditional formal text. we consider the task of NER on microblog text. In this paper, we propose a Convolutional Neural Network for NER in Chinese microblog text. Instead of traditional machine learning needing man-made input features carefully optimized for NER task, our system learns the words feature by itself. Our network uses a sliding window of word context to predict tags. Experimental results show that our model achieved 80% accuracy on this task.
基于卷积神经网络的中文微博命名实体识别
命名实体识别(NER)通常关注于传统的正式文本。我们考虑了微博文本的NER任务。在本文中,我们提出了一种卷积神经网络用于中文微博文本的NER。传统的机器学习需要人为的输入特征,而不是为NER任务精心优化,我们的系统可以自己学习单词特征。我们的网络使用单词上下文的滑动窗口来预测标签。实验结果表明,我们的模型在此任务上达到了80%的准确率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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