Team JKU-AIWarriors in the ACM Recommender Systems Challenge 2021: Lightweight XGBoost Recommendation Approach Leveraging User Features

Publikation: Beitrag in Buch/Bericht/Konferenzband › Konferenzbeitrag › Begutachtung

Originalsprache	Englisch
Titel	Proceedings of the RecSys Challenge Workshop 2021 at the 15th ACM Conference on Recommender Systems (RecSys 2021)
Seitenumfang	10
Publikationsstatus	Veröffentlicht - 2021

Wissenschaftszweige

@inproceedings{3315916cce4a418a8232f3c1f79e9dac,

title = "Team JKU-AIWarriors in the ACM Recommender Systems Challenge 2021: Lightweight XGBoost Recommendation Approach Leveraging User Features",

author = "A. Krauck and David Penz and Markus Schedl",

year = "2021",

language = "English",

booktitle = "Proceedings of the RecSys Challenge Workshop 2021 at the 15th ACM Conference on Recommender Systems (RecSys 2021)",

}

Publikation: Beitrag in Buch/Bericht/Konferenzband › Konferenzbeitrag › Begutachtung

TY - GEN

T1 - Team JKU-AIWarriors in the ACM Recommender Systems Challenge 2021: Lightweight XGBoost Recommendation Approach Leveraging User Features

AU - Krauck, A.

AU - Penz, David

AU - Schedl, Markus

PY - 2021

Y1 - 2021

M3 - Conference proceedings

BT - Proceedings of the RecSys Challenge Workshop 2021 at the 15th ACM Conference on Recommender Systems (RecSys 2021)

ER -