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Found 7 papers, 0 papers with code
Incorporating Higher-order Structural Information for Graph Clustering
In recent years, graph convolutional network (GCN) has emerged as a powerful tool for deep clustering, integrating both graph structural information and node attributes.
Modeling Multi-aspect Preferences and Intents for Multi-behavioral Sequential Recommendation
To extract multi-aspect preferences from target behaviors, we propose a multi-aspect projection mechanism for generating multiple preference representations from multiple aspects.
Incorporating Heterogeneous User Behaviors and Social Influences for Predictive Analysis
An unsupervised way to construct a social behavior graph based on spatio-temporal data and to model social influences is proposed.
Deep Meta-learning in Recommendation Systems: A Survey
For each recommendation scenario, we further discuss technical details about how existing methods apply meta-learning to improve the generalization ability of recommendation models.
A Survey on Cross-domain Recommendation: Taxonomies, Methods, and Future Directions
In this survey paper, we first proposed a two-level taxonomy of cross-domain recommendation which classifies different recommendation scenarios and recommendation tasks.
Jointly Modeling Heterogeneous Student Behaviors and Interactions Among Multiple Prediction Tasks
In this paper, we focus on modeling heterogeneous behaviors and making multiple predictions together, since some prediction tasks are related and learning the model for a specific task may have the data sparsity problem.
Multi-Target Deep Learning for Algal Detection and Classification
Water quality has a direct impact on industry, agriculture, and public health.
