Title
BLAC: A Named Entity Recognition Model Incorporating Part-of-Speech Attention in Irregular Short Text
Abstract
Irregular text refers to text with incomplete sequence information of the sentence or text that does not meet normal grammatical specifications, such as Weibo text. Existing named entity recognition algorithms recognize such text, the effect is poor due to the lack of context information. Because the attention mechanism has advantages in obtaining contextual information, we merge part-of-speech attention with the BI-LSTM-CRF model and propose a BLAC model. We tested on several public datasets and compared the results with the basic model BI-LSTM-CRF. The results show that the method we proposed has a certain improvement in the entity recognition of irregular short text.
Year
DOI
Venue
2020
10.1109/RCAR49640.2020.9303256
2020 IEEE International Conference on Real-time Computing and Robotics (RCAR)
Keywords
DocType
ISBN
POS attention model,Named entity recognition,Irregular short text,BI-LSTM-CRF,BLAC
Conference
978-1-7281-7294-1
Citations 
PageRank 
References 
0
0.34
6
Authors
4
Name
Order
Citations
PageRank
Ming Zhu100.34
Huakang Li201.01
Xiaoyu Sun39516.54
Zhuo Yang400.34