基于LSTM和部首嵌入的古汉语句子分割

Oct, 2018

Sentence Segmentation for Classical Chinese Based on LSTM with Radical Embedding

Xu Han, Hongsu Wang, Sanqian Zhang, Qunchao Fu, Jun S. Liu

TL;DR本文提出了基于偏旁部首的低维特征嵌入方法，配合LSTM模型用于古代汉语文本的句子分割，实验结果表明，相较于已有方法，在汉文句子分割上取得了更好的效果，尤其是唐代碑文的处理。

Abstract

In this paper, we develop a low than character feature embedding called radical embedding, and apply it on lstm model for sentence segmentation