"Recommendation"的相关文档

Towards Open-World Recommendation An Inductive Model-based Collaborative Filtering Approach
TowardsOpen-WorldRecommendation:AnInductiveModel-basedCollaborativeFilteringApproachQitianWu12HengruiZhang1XiaofengGao12JunchiYan12HongyuanZha3Abstract(MC)whereonehasauser-itemratingmatrixwhoseentr...
An Model-Based Collaborative Towards Inductive
2023-11-16 19:42:1119151.02 MB27
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Correcting Exposure Bias for Link Recommendation
CorrectingExposureBiasforLinkRecommendationShantanuGupta12HaoWang3ZacharyLipton2YuyangWang4Abstractconcernsaboutexposurebias—manymissinglinksarefalsenegatives,anddidnotformduetolackofexposurerathe...
for Bias Correcting Recommendation Link
2023-11-16 18:30:521884395.59 KB23
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Ordinal Non-negative Matrix Factorization for Recommendation
OrdinalNon-negativeMatrixFactorizationforRecommendationOlivierGouvert1ThomasOberlin2CédricFévotte1Abstract2011)whichaimstopredictfutureinteractionsbetweenusersanditemsinordertomakeRecommendations...
for Matrix Ordinal Factorization Non-negative
2023-11-14 21:45:461529579.22 KB30
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Graph Convolutional Network for Recommendation with Low-pass Collaborative Filters
GraphConvolutionalNetworkforRecommendationwithLow-passCollaborativeFiltersWenhuiYu1ZhengQin12Abstractthesignalofeachnodewithitsneighborhoods(Zhouetal.,2018).Byconstrainingthekernel,GCNslosetheabili...
for with Graph Convolutional Network
2023-11-14 21:44:251234930.41 KB26
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Doubly Robust Joint Learning for Recommendation on Data Missing Not at Random
DoublyRobustJointLearningforRecommendationonDataMissingNotatRandomXiaojieWang1RuiZhang1YuSun2JianzhongQi1Abstract(MNAR).Forexample,arecentstudyinsongrecommen-dationshowsthattheprobabilityofaratingb...
Learning for on Robust Joint
2023-11-13 14:46:58848337.84 KB20
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Towards Open-World Recommendation An Inductive Model-based Collaborative Filtering Approach

Correcting Exposure Bias for Link Recommendation

Ordinal Non-negative Matrix Factorization for Recommendation

Graph Convolutional Network for Recommendation with Low-pass Collaborative Filters

Doubly Robust Joint Learning for Recommendation on Data Missing Not at Random