Aligning distillation for cold-start item recommendation

F Huang, Z Wang, X Huang, Y Qian, Z Li… - Proceedings of the 46th …, 2023‏ - dl.acm.org
Recommending cold items in recommendation systems is a longstanding challenge due to
the inherent differences between warm items, which are recommended based on user …

Mines: Message intercommunication for inductive relation reasoning over neighbor-enhanced subgraphs

K Liang, L Meng, S Zhou, W Tu, S Wang, Y Liu… - Proceedings of the …, 2024‏ - ojs.aaai.org
GraIL and its variants have shown their promising capacities for inductive relation reasoning
on knowledge graphs. However, the uni-directional message-passing mechanism hinders …

Macro graph neural networks for online billion-scale recommender systems

H Chen, Y Bei, Q Shen, Y Xu, S Zhou… - Proceedings of the …, 2024‏ - dl.acm.org
Predicting Click-Through Rate (CTR) in billion-scale recommender systems poses a long-
standing challenge for Graph Neural Networks (GNNs) due to the overwhelming …

Multi-factor sequential re-ranking with perception-aware diversification

Y Xu, H Chen, Z Wang, J Yin, Q Shen, D Wang… - Proceedings of the 29th …, 2023‏ - dl.acm.org
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 …

Generative adversarial framework for cold-start item recommendation

H Chen, Z Wang, F Huang, X Huang, Y Xu… - Proceedings of the 45th …, 2022‏ - dl.acm.org
The cold-start problem has been a long-standing issue in recommendation. Embedding-
based recommendation models provide recommendations by learning embeddings for each …

[HTML][HTML] Portable graph-based rumour detection against multi-modal heterophily

TT Nguyen, Z Ren, TT Nguyen, J Jo… - Knowledge-Based …, 2024‏ - Elsevier
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 …

Group-based fraud detection network on e-commerce platforms

J Yu, H Wang, X Wang, Z Li, L Qin, W Zhang… - Proceedings of the 29th …, 2023‏ - dl.acm.org
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 …

Beyond the overlap** users: cross-domain recommendation via adaptive anchor link learning

Y Zhao, C Li, J Peng, X Fang, F Huang… - Proceedings of the 46th …, 2023‏ - dl.acm.org
Cross-Domain Recommendation (CDR) is capable of incorporating auxiliary information
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 …

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 …