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
Optimizing Neighborhoods for Fair Top-N Recommendation:
, In:
Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization
,
Eleftherakis, Stavroula
;
Koutrika, Georgia
;
Amer-Yahia, Sihem
- p. 57-66 , 2024
Link:
https://dl.acm.org/doi/10.1145/3627043.3659539
RT T1 <cTitle>Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization</cTitle>: T1 <Title>Optimizing Neighborhoods for Fair Top-N Recommendation</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3659539&Exemplar=1&LAN=DE A1 Eleftherakis, Stavroula A1 Koutrika, Georgia A1 Amer-Yahia, Sihem PB ACM YR 2024 K1 balanced neighborhoods K1 collaborative filtering K1 fairness K1 neighborhood learning K1 recommender systems K1 sparse linear models K1 Computing methodologies K1 Machine learning K1 Machine learning approaches K1 Learning linear models K1 Information systems K1 Information retrieval K1 Retrieval tasks and goals K1 Recommender systems SP 57 OP 66 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3627043.3659539 DO https://dl.acm.org/doi/10.1145/3627043.3659539 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
