Knowledge Commons of Institute of Automation,CAS
Convolutional Neural Network with Word Embeddings for Chinese Word Segmentation | |
Wang CQ(汪春奇); Xu B(徐波) | |
2017 | |
会议名称 | 第八届国际自然语言处理研讨会 |
页码 | 163-172 |
会议日期 | 2017年11月 |
会议地点 | 台北 |
摘要 | Character-based sequence labeling frame- work is flexible and efficient for Chi- nese word segmentation (CWS). Recently, many character-based neural models have been applied to CWS. While they obtain good performance, they have two obvious weaknesses. The first is that they heav- ily rely on manually designed bigram fea- ture, i.e. they are not good at captur- ing n-gram features automatically. The second is that they make no use of full word information. For the first weakness, we propose a convolutional neural model, which is able to capture rich n-gram fea- tures without any feature engineering. For the second one, we propose an effective approach to integrate the proposed model with word embeddings. We evaluate the model on two benchmark datasets: PKU and MSR. Without any feature engineer- ing, the model obtains competitive per- formance — 95.7% on PKU and 97.3% on MSR. Armed with word embeddings, the model achieves state-of-the-art perfor- mance on both datasets — 96.5% on PKU and 98.0% on MSR, without using any ex- ternal labeled resource. |
关键词 | Chinese Word Segmentation Convolutional Neural Network Word Embedding |
收录类别 | EI |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/41050 |
专题 | 复杂系统认知与决策实验室_听觉模型与认知计算 |
推荐引用方式 GB/T 7714 | Wang CQ,Xu B. Convolutional Neural Network with Word Embeddings for Chinese Word Segmentation[C],2017:163-172. |
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