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Taylor & Francis
Connection Science
,  том 35 ,  издание 1

Lightweight multilayer interactive attention network for aspect-based sentiment analysis

Тип публикации: Journal Article
Дата публикации: 2023-04-03
Taylor & Francis
scimago Q2
wos Q2
БС2
SJR: 0.681
CiteScore: 9.5
Impact factor: 3.4
ISSN: 09540091, 13600494
Artificial Intelligence
Software
Human-Computer Interaction
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Zheng W. et al. Lightweight multilayer interactive attention network for aspect-based sentiment analysis // Connection Science. 2023. Vol. 35. No. 1.
ГОСТ со всеми авторами (до 50) Скопировать
Zheng W., Zhang S., Yang C., Hu P. Lightweight multilayer interactive attention network for aspect-based sentiment analysis // Connection Science. 2023. Vol. 35. No. 1.
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TY - JOUR
DO - 10.1080/09540091.2023.2189119
UR - https://doi.org/10.1080/09540091.2023.2189119
TI - Lightweight multilayer interactive attention network for aspect-based sentiment analysis
T2 - Connection Science
AU - Zheng, Wenjun
AU - Zhang, Shunxiang
AU - Yang, Cheng
AU - Hu, Peng
PY - 2023
DA - 2023/04/03
PB - Taylor & Francis
IS - 1
VL - 35
SN - 0954-0091
SN - 1360-0494
ER -
BibTex
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@article{2023_Zheng,
author = {Wenjun Zheng and Shunxiang Zhang and Cheng Yang and Peng Hu},
title = {Lightweight multilayer interactive attention network for aspect-based sentiment analysis},
journal = {Connection Science},
year = {2023},
volume = {35},
publisher = {Taylor & Francis},
month = {apr},
url = {https://doi.org/10.1080/09540091.2023.2189119},
number = {1},
doi = {10.1080/09540091.2023.2189119}
}