I agree that this site is using cookies. You can find further informations
here
.
X
Login
Merkliste (
0
)
Home
About us
Home About us
Our history
Profile
Press & public relations
Friends
The library in figures
Exhibitions
Projects
Training, internships, careers
Films
Services & Information
Home Services & Information
Lending and interlibrary loans
Returns and renewals
Training and library tours
My Account
Library cards
New to the library?
Download Information
Opening hours
Learning spaces
PC, WLAN, copy, scan and print
Catalogs and collections
Home Catalogs and Collections
Rare books and manuscripts
Digital collections
Subject Areas
Our sites
Home Our sites
Central Library
Law Library (Juridicum)
BB Business and Economics (BB11)
BB Physics and Electrical Engineering
TB Engineering and Social Sciences
TB Economics and Nautical Sciences
TB Music
TB Art & Design
TB Bremerhaven
Contact the library
Home Contact the library
Staff Directory
Open access & publishing
Home Open access & publishing
Reference management: Citavi & RefWorks
Publishing documents
Open Access in Bremen
zur Desktop-Version
Toggle navigation
Merkliste
1 Ergebnisse
1
SSK-DNN: Semantic and Sentiment Knowledge for Incremental T..:
, In:
2023 IEEE International Conference on Data Mining Workshops (ICDMW)
,
Khan, Jawad
;
Ahmad, Niaz
;
Choi, Chanyeok
... - p. 52-59 , 2023
Link:
https://doi.org/10.1109/ICDMW60847.2023.00016
RT T1 <cTitle>2023 IEEE International Conference on Data Mining Workshops (ICDMW)</cTitle>: T1 <Title>SSK-DNN: Semantic and Sentiment Knowledge for Incremental Text Sentiment Classification</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10411605&Exemplar=1&LAN=DE A1 Khan, Jawad A1 Ahmad, Niaz A1 Choi, Chanyeok A1 Ullah, Saif A1 Kim, Gyurin A1 Lee, Youngmoon YR 2023 SN 2375-9259 K1 Deep learning K1 Sentiment analysis K1 Semantics K1 Feature extraction K1 Noise measurement K1 Task analysis K1 Principal component analysis K1 Sentiment Analysis K1 Incremental Learning K1 Wide Coverage Sentiment Lexicons K1 Linguistic Rules K1 Sentiment-enhanced word embeddings K1 Context SP 52 OP 59 LK http://dx.doi.org/https://doi.org/10.1109/ICDMW60847.2023.00016 DO https://doi.org/10.1109/ICDMW60847.2023.00016 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
