Search Result

1

Chinese nested named entity recognition based on vocabulary fusion and span detection

基于词融合与跨度检测的中文嵌套命名实体识别

Chen Shuzhen

Dou Quansheng

Tang Huanling

Jiang Ping

Chinese nested named entity recognition

BERT model

multi-word fusion

span boundary detection

No. 8, 2023 : 2382-2386,2392 doi:10.19734/j.issn.1001-3695.2022.11.0767

2

Named entity recognition in motor field based on BERT and multi-window gated CNN

基于BERT和多窗口门控CNN的电机领域命名实体识别

Zhang Zhiyuan

Sun Shuihua

Xu Shi'ao

Xu Fan

Liu Jianhua

named entity recognition

motor field

BERT model

multi-window gated CNN

BiLSTM model

No. 1, 2023 : 107-114 doi:10.19734/j.issn.1001-3695.2022.05.0278

3

Code snippets recommendation based on SBERT model

基于SBERT模型的代码片段推荐

Deng Siyuan

Wei Le

Shu Hongping

code reuse

code corpus

deep learning

code snippets recommendation

No. 12, 2022 : 3730-3735 doi:10.19734/j.issn.1001-3695.2022.05.0242

4

Handling contrastive sentences in sentiment analysis based on attention network

基于注意力网络的情感分析中的对比句处理

Zhang Rong

Liu Yuan

Li Yang

aspect-level sentiment analysis

contrastive sentences

attention network

BERT model

relative position encoding

No. 9, 2022 : 2695-2700,2716 doi:10.19734/j.issn.1001-3695.2022.02.0052

5

Aspect-level sentiment analysis based on double-layer part-of-speech-aware and multi-head interactive attention mechanism

基于双层词性感知和多头交互注意机制的方面级情感分析

Xue Fang

Guo Yi

Li Zhiqiang

Wang Jiahui

BERT model

double-layer part-of-speech-aware

interactive features

dynamic feature fusion

No. 3, 2022 : 704-710 doi:10.19734/j.issn.1001-3695.2021.08.0340

Search BERT model

SearchBERT modelreturned 5 results

Chinese nested named entity recognition based on vocabulary fusion and span detection

Named entity recognition in motor field based on BERT and multi-window gated CNN

Code snippets recommendation based on SBERT model

Handling contrastive sentences in sentiment analysis based on attention network

Aspect-level sentiment analysis based on double-layer part-of-speech-aware and multi-head interactive attention mechanism