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MultiBiSage: bipartite-view fusion for heterogeneous recommendation graphs

Contribution grade

Scalable heterogeneous graph recommendation · Human-designed research method or resource

Reference score60,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Decomposed heterogeneous entity interactions into bipartite views, aggregated each view's sampled visual/textual neighborhood with a Transformer and fused the resulting view embeddings through another attention layer.

Scientific scope

Decomposed heterogeneous entity interactions into bipartite views, aggregated each view's sampled visual/textual neighborhood with a Transformer and fused the resulting view embeddings through another attention layer. A distinct heterogeneous-view fusion extension, not another count for PinSage deployment or its original sampler. Reuses Pixie and distributed data workflows. View decomposition, stored neighborhoods and selected losses constrain expressiveness and cost; v1's template DOI/venue placeholders are not exported as valid publication facts.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. A distinct heterogeneous-view fusion extension, not another count for PinSage deployment or its original sampler. Reuses Pixie and distributed data workflows. View decomposition, stored neighborhoods and selected losses constrain expressiveness and cost; v1's template DOI/venue placeholders are not exported as valid publication facts.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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