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Found 4 papers, 1 papers with code
A Counterfactual Collaborative Session-based Recommender System
Next, COCO-SBRS adopts counterfactual inference to recommend items based on the outputs of the pre-trained recommendation model considering the causalities to alleviate the data sparsity problem.
Next-item Recommendations in Short Sessions
The obtained similar sessions are then utilized to complement and optimize the preference representation learned from the current short session by the local module for more accurate next-item recommendations in this short session.
A Block-based Generative Model for Attributed Networks Embedding
To preserve the attribute information, we assume that each node has a hidden embedding related to its assigned block.
Hyperbolic Node Embedding for Signed Networks
Signed network embedding methods aim to learn vector representations of nodes in signed networks.
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