开始发作
发表于 2025-3-25 05:26:35
S2DNMF: A Self-supervised Deep Nonnegative Matrix Factorization Recommendation Model Incorporating Dem, this paper proposes a recommendation model based on deep nonnegative matrix factorization (Self-supervised Deep Nonnegative Matrix Factorization, .), which inherits the advantages of the self-supervised model, combines deep attribute fusion features of network structure, integrates network topol
脆弱么
发表于 2025-3-25 10:18:27
S2DNMF: A Self-supervised Deep Nonnegative Matrix Factorization Recommendation Model Incorporating Dem, this paper proposes a recommendation model based on deep nonnegative matrix factorization (Self-supervised Deep Nonnegative Matrix Factorization, .), which inherits the advantages of the self-supervised model, combines deep attribute fusion features of network structure, integrates network topol
notice
发表于 2025-3-25 13:53:38
Self-filtering Residual Attention Network Based on Multipair Information Fusion for Session-Based Res (i.e., interaction) to predict the next interact item in the session. However, under the auspices of user anonymity and short activity durations, data sparsity is a significant problem for these models. Moreover, given that human users rarely follow a scripted session, many noisy interact items ca
减至最低
发表于 2025-3-25 19:26:41
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断言
发表于 2025-3-25 23:04:31
TransRec: Learning Transferable Recommendation from Mixture-of-Modality Feedbackr, current recommendation methods often rely on categorical identity features that cannot be shared between different platforms, making fine-tuning models for new scenarios challenging. Displayed content on these platforms often contain multimedia information, leading to a mixture-of-modality (MoM)
spinal-stenosis
发表于 2025-3-26 02:23:10
TransRec: Learning Transferable Recommendation from Mixture-of-Modality Feedbackr, current recommendation methods often rely on categorical identity features that cannot be shared between different platforms, making fine-tuning models for new scenarios challenging. Displayed content on these platforms often contain multimedia information, leading to a mixture-of-modality (MoM)
travail
发表于 2025-3-26 05:16:37
VM-Rec: A Variational Mapping Approach for Cold-Start User Recommendationiciency in auxiliary content information for users. Furthermore, most methods often require simultaneous updates to extensive parameters of recommender models, resulting in high training costs, especially in large-scale industrial scenarios. We observe that the model can generate expressive embeddin
NEEDY
发表于 2025-3-26 09:34:10
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使残废
发表于 2025-3-26 14:43:19
Matching Tabular Data to Knowledge Graph Based on Multi-level Scoring Filters for Table Entity Disamee tasks: Column Type Annotation (CTA), Cell Entity Annotation (CEA), and Columns Property Annotation (CPA). It is a non-trivial task due to missing, incomplete, or ambiguous metadata, which makes entity disambiguation more difficult. Previous approaches mostly are based on two representative paradi
生命层
发表于 2025-3-26 19:43:05
Matching Tabular Data to Knowledge Graph Based on Multi-level Scoring Filters for Table Entity Disamee tasks: Column Type Annotation (CTA), Cell Entity Annotation (CEA), and Columns Property Annotation (CPA). It is a non-trivial task due to missing, incomplete, or ambiguous metadata, which makes entity disambiguation more difficult. Previous approaches mostly are based on two representative paradi