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• W3129482887 abstract "Knowledge graph (KG) plays an increasingly important role in recommender systems. A recent technical trend is to develop end-to-end models founded on graph neural networks (GNNs). However, existing GNN-based models are coarse-grained in relational modeling, failing to (1) identify user-item relation at a fine-grained level of intents, and (2) exploit relation dependencies to preserve the semantics of long-range connectivity." @default.
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• W3129482887 date "2021-04-19" @default.
• W3129482887 modified "2023-10-16" @default.
• W3129482887 title "Learning Intents behind Interactions with Knowledge Graph for Recommendation" @default.
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• W3129482887 doi "https://doi.org/10.1145/3442381.3450133" @default.
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