Feb 13, 2024 · In this article, we propose a swarm self-supervised hypergraph embedding (SHE) model to predict users' interests by hypergraph convolution and self-supervised ...
Feb 13, 2024 · Experiments on public datasets show that the proposed SHE outperforms the state-of-the-art models demonstrating the effectiveness of hypergraph- ...
Swarm Self-supervised Hypergraph Embedding for Recommendation
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Oct 22, 2024 · Experiments on public datasets show that the proposed SHE outperforms the state-of-the-art models demonstrating the effectiveness of hypergraph- ...
为了有效地保存、管理机构知识资产；最大限度彰显、提升机构及其学者在全球的学术影响力，图书馆构建了机构知识门户——一种基于全球开放理念的新型知识组织与传播的门户， ...
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Jul 28, 2022 · To further enhance the graph-based user-item interaction modeling, some follow-up studies propose to learn intent-aware representations with ...
Missing: Swarm | Show results with:Swarm
We propose a novel framework called self-supervised hypergraph learning for knowledge-aware social recommendation (SHLKR).
Missing: Swarm | Show results with:Swarm
It follows an auxiliary local view by similar hypergraph construction and interest propagation to restrain unnecessary propagation between user swarms. Besides, ...
By stacking multiple layers in the hypergraph channel, we can borrow the strengths of hypergraph convolution to gen- erate high-quality recommendation results.
Missing: Swarm | Show results with:Swarm
Jul 28, 2022 · In this paper, we propose SHT, a novel Self-Supervised Hypergraph Transformer framework (SHT) which augments user representations by exploring the global ...
Missing: Swarm | Show results with:Swarm