wsdm-23 paper: multi-intention oriented contrastive learning for sequential recommendation
Published 1 year ago • 74 plays • Length 11:50Download video MP4
Download video MP3
Similar videos
-
11:08
wsdm-23 paper: knowledge enhancement for contrastive multi-behavior recommendation
-
12:54
wsdm-23 paper: towards universal cross-domain recommendation
-
12:48
wsdm-23 paper: efficiently leveraging multi-level user intent for session-based recommendation
-
14:07
wsdm-23 paper: dynamic intent guided meta network for differentiated user engagement forecasting
-
9:17
wsdm-23 paper: counterfactual collaborative reasoning
-
10:15
wsdm-23 paper: federated unlearning for on-device recommendation
-
11:31
wsdm-23 paper: a multi-graph fusion based spatiotemporal dynamic learning framework
-
10:03
wsdm-23 paper:minimum entropy principle guided graph neural networks
-
11:38
wsdm-23 paper: relation preference oriented high-order sampling for recommendation
-
12:59
wsdm-23 paper: mix-moment graph neural network towards modeling neighborhood feature distribution
-
11:43
wsdm-23 paper: one for all, all for one: learning and transferring user embeddings
-
16:48
wsdm-23 paper: demetris: counting (near)-cliques by crawling
-
10:56
wsdm-23 paper:simultaneous linear multi-view attributed graph representation learning and clustering
-
11:15
wsdm-23 paper: s2tul: a semi-supervised framework for trajectory-user linking
-
10:16
wsdm-23 paper: learning to distinguish multi-user coupling behaviors for tv recommendation
-
12:08
wsdm-23 paper: visual matching is enough for scene text retrieval
-
11:32
wsdm-23 paper: disentangled negative sampling for collaborative filtering
-
11:46
wsdm-23 paper:graph explicit neural networks