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Aligning distillation for cold-start item recommendation
Recommending cold items in recommendation systems is a longstanding challenge due to
the inherent differences between warm items, which are recommended based on user …
the inherent differences between warm items, which are recommended based on user …
Mines: Message intercommunication for inductive relation reasoning over neighbor-enhanced subgraphs
GraIL and its variants have shown their promising capacities for inductive relation reasoning
on knowledge graphs. However, the uni-directional message-passing mechanism hinders …
on knowledge graphs. However, the uni-directional message-passing mechanism hinders …
Macro graph neural networks for online billion-scale recommender systems
Predicting Click-Through Rate (CTR) in billion-scale recommender systems poses a long-
standing challenge for Graph Neural Networks (GNNs) due to the overwhelming …
standing challenge for Graph Neural Networks (GNNs) due to the overwhelming …
Multi-factor sequential re-ranking with perception-aware diversification
Feed recommendation systems, which recommend a sequence of items for users to browse
and interact with, have gained significant popularity in practical applications. In feed …
and interact with, have gained significant popularity in practical applications. In feed …
Generative adversarial framework for cold-start item recommendation
The cold-start problem has been a long-standing issue in recommendation. Embedding-
based recommendation models provide recommendations by learning embeddings for each …
based recommendation models provide recommendations by learning embeddings for each …
[HTML][HTML] Portable graph-based rumour detection against multi-modal heterophily
The propagation of rumours on social media poses an important threat to societies, so that
various techniques for graph-based rumour detection have been proposed recently. Existing …
various techniques for graph-based rumour detection have been proposed recently. Existing …
Group-based fraud detection network on e-commerce platforms
Along with the rapid technological and commercial innovation on the e-commerce platforms,
there are an increasing number of frauds that bring great harm to these platforms. Many …
there are an increasing number of frauds that bring great harm to these platforms. Many …
Beyond the overlap** users: cross-domain recommendation via adaptive anchor link learning
Cross-Domain Recommendation (CDR) is capable of incorporating auxiliary information
from multiple domains to advance recommendation performance. Conventional CDR …
from multiple domains to advance recommendation performance. Conventional CDR …
Mpgaan: Effective and efficient heterogeneous information network classification
Z Wu - Journal of Computer Science and Technology Studies, 2024 - neliti.com
In this paper, we propose a novel Graph Neural Network (GNN) model named" Meta-Path
Guided Attention Aggregation Network"(MPAAGN), which is specifically designed for graph …
Guided Attention Aggregation Network"(MPAAGN), which is specifically designed for graph …
KSTAGE: A knowledge-guided spatial-temporal attention graph learning network for crop yield prediction
M Qiao, X He, X Cheng, P Li, Q Zhao, C Zhao… - Information Sciences, 2023 - Elsevier
Accurate and timely crop yield prediction is difficult to achieve due to the nonlinear and
dynamic spatial–temporal correlations included during the crop growth process. The latest …
dynamic spatial–temporal correlations included during the crop growth process. The latest …