Tibetan location Name Recognition Based on BiLSTM-CRF Model

被引：3
|
作者：
Ma, Wei [1 ]
Yu, Hongzhi [1 ]
Zhao, Kun [1 ]
Zhao, Deshun [1 ]
Yang, Jun [1 ]
Ma, Jing [2 ]
机构：
[1] Northwest Minzu Univ, Minist Educ, Key Lab Chinas Ethn Languages & Informat Technol, Lanzhou, Peoples R China
[2] Gansu Polit Sci & Law Univ, Personnel Dept, Lanzhou, Peoples R China
来源：
2019 INTERNATIONAL CONFERENCE ON CYBER-ENABLED DISTRIBUTED COMPUTING AND KNOWLEDGE DISCOVERY (CYBERC) | 2019年
关键词：
BiLSTM; CRF; Tibetan location name; Location name Recognition; TIME;
D O I：
10.1109/CyberC.2019.00077
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Tibetan location name recognition is an important research topic in Tibetan information processing. In this paper, we attempt to construct a neural network model based on BiLSTM-CRF framework for location name recognition. In the experiment, for the public dataset of Tibetan location name, the model obtains the context information of the current word in the BiLSTM layer, decodes the output of the BiLSTM layer in the CRF layer, and finally outputs the tag sequence. The experiment proves the validity of the framework and obtains good experimental results, and the results show that the model outperforms competitive the traditional method, and improved the F-measure without resorting to any language-specific knowledge or resources.
引用
收藏
页码：412 / 416
页数：5
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