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
Improving One-class Recommendation with Multi-tasking on Va..:
, In:
Fourteenth ACM Conference on Recommender Systems
,
Shao, Chu-Jen
;
Fu, Hao-Ming
;
Cheng, Pu-Jen
- p. 498-502 , 2020
Link:
https://dl.acm.org/doi/10.1145/3383313.3412224
RT T1
Fourteenth ACM Conference on Recommender Systems
: T1
Improving One-class Recommendation with Multi-tasking on Various Preference Intensities
UL https://suche.suub.uni-bremen.de/peid=acm-3412224&Exemplar=1&LAN=DE A1 Shao, Chu-Jen A1 Fu, Hao-Ming A1 Cheng, Pu-Jen PB ACM YR 2020 K1 collaborative filtering K1 graph convolutional network K1 implicit feedback K1 one-class recommendation K1 Information systems K1 Information retrieval K1 Retrieval tasks and goals K1 Recommender systems SP 498 OP 502 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3383313.3412224 DO https://dl.acm.org/doi/10.1145/3383313.3412224 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)