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
Research on Belt and Road Big Data Visualization Based on T..:
, In:
2020 6th International Conference on Robotics and Artificial Intelligence
,
Wen, Yana
;
Wei, Tingyue
;
Cui, Kewei
... - p. 121-125 , 2020
Link:
https://dl.acm.org/doi/10.1145/3449301.3449322
RT T1 <cTitle>2020 6th International Conference on Robotics and Artificial Intelligence</cTitle>: T1 <Title>Research on Belt and Road Big Data Visualization Based on Text Clustering Algorithm</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3449322&Exemplar=1&LAN=DE A1 Wen, Yana A1 Wei, Tingyue A1 Cui, Kewei A1 Ling, Bai A1 Zhang, Yahao A1 Huang, Meng PB ACM YR 2020 K1 Keywords-component K1 One Belt One Road K1 Text clustering algorithm K1 big data visualization SP 121 OP 125 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3449301.3449322 DO https://dl.acm.org/doi/10.1145/3449301.3449322 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
