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Graph Learning Augmented Heterogeneous Graph Neural Network for Social Recommendation
Social recommendation based on social network has achieved great success in improving the performance of the recommendation system. Since social network (user-user relations) and user-item interactions are both naturally represented as graph-structured ...
Deconfounded Causal Collaborative Filtering
Recommender systems may be confounded by various types of confounding factors (also called confounders) that may lead to inaccurate recommendations and sacrificed recommendation performance. Current approaches to solving the problem usually design each ...
Examining the User Evaluation of Multi-List Recommender Interfaces in the Context of Healthy Recipe Choices
Multi-list recommender systems have become widespread in entertainment and e-commerce applications. Yet, extensive user evaluation research is missing. Since most content is optimized toward a user’s current preferences, this may be problematic in ...
Learning Hierarchical Spatial Tasks with Visiting Relations for Next POI Recommendation
Sparsity is an established problem for the next Point-of-Interest (POI) recommendation task, where it hinders effective learning of user preferences from the User-POI matrix. However, learning multiple hierarchically related spatial tasks, and visiting ...