Recommendation Systems
A recommendation system is a technology that leverages user behavior data, preference information, and item features to predict users' interest in items through algorithmic models. Its core objective is to optimize the user experience, enhance user satisfaction and platform stickiness, while also increasing business conversion rates and revenue. Recommendation systems are widely used in e-commerce, social media, online video, and music streaming platforms, among others, to effectively match user needs with platform resources, achieving efficient information filtering and value delivery.
∞-AE
TransCF
EASE
FedPerGNN
scaled-CER
GLocal-K
HSTU
H+Vamp Gated
GRALS
HAKG
ProxyRCA
HSTU+MoL
LT-OCF
Multi-Gradient Descent
HGN
ProxyRCA
CARCA
CARCA Learnt + Con
HetroFair
TLSAN
CFM
KGNN-LS
KTUP (soft)
TransCF
KGNN-LS
GLocal-K
DANSER
SR-PredAO(SGNN-HN)
IGMC
INN
HGN
HGN
NESCL
Ekar*
RATE-CSE
SASRec
NGNN
KERL
SASRec
DANSER
MG-GAT
ConvNCF
SVD-AE