文献
J-GLOBAL ID:202202232165655205
整理番号:22A0788177
ERNIE-BiGRU-Attentionに基づくルモール検出のための効果的なアプローチ【JST・京大機械翻訳】
An Effective Approach for Rumor Detection Based on ERNIE-BiGRU-Attention
著者 (4件):
Lan Tian
(Ministry of Education College of Cyberspace Security, Beijing University of Posts and Telecommunications,Key Laboratory of Trustworthy Distributed Computing and Service (BUPT),Beijing,China)
,
Li Xiaoyong
(Ministry of Education College of Cyberspace Security, Beijing University of Posts and Telecommunications,Key Laboratory of Trustworthy Distributed Computing and Service (BUPT),Beijing,China)
,
Gao Yali
(Ministry of Education College of Cyberspace Security, Beijing University of Posts and Telecommunications,Key Laboratory of Trustworthy Distributed Computing and Service (BUPT),Beijing,China)
,
Yuan Jie
(Ministry of Education College of Cyberspace Security, Beijing University of Posts and Telecommunications,Key Laboratory of Trustworthy Distributed Computing and Service (BUPT),Beijing,China)
資料名:
IEEE Conference Proceedings
(IEEE Conference Proceedings)
巻:
2022
号:
ICCECE
ページ:
859-862
発行年:
2022年
JST資料番号:
W2441A
資料種別:
会議録 (C)
記事区分:
原著論文
発行国:
アメリカ合衆国 (USA)
言語:
英語 (EN)