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1 Ergebnisse
1
Lightweight Model for Session-Based Recommender Systems wit..:
, In:
RecSys Challenge 2022
,
Della Volpe, Nicola
;
Mainetti, Lorenzo
;
Martignetti, Alessio
... - p. 18-23 , 2022
Link:
https://dl.acm.org/doi/10.1145/3556702.3556829
RT T1
RecSys Challenge 2022
: T1
Lightweight Model for Session-Based Recommender Systems with Seasonality Information in the Fashion Domain
UL https://suche.suub.uni-bremen.de/peid=acm-3556829&Exemplar=1&LAN=DE A1 Della Volpe, Nicola A1 Mainetti, Lorenzo A1 Martignetti, Alessio A1 Menta, Andrea A1 Pala, Riccardo A1 Polvanesi, Giacomo A1 Sammarco, Francesco A1 Perez Maurera, Fernando Benjamin A1 Bernardis, Cesare A1 Ferrari Dacrema, Maurizio PB ACM YR 2022 K1 boosting K1 feature engineering K1 neural networks K1 recommender systems K1 recsys challenge K1 Theory of computation K1 Theory and algorithms for application domains K1 Machine learning theory K1 Boosting K1 Information systems K1 Information retrieval K1 Retrieval models and ranking K1 Learning to rank SP 18 OP 23 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3556702.3556829 DO https://dl.acm.org/doi/10.1145/3556702.3556829 SF ELIB - SuUB Bremen
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