PHKT uses personalized dynamic hypergraphs and KAN-Transformer to outperform baselines in multi-behavior sequential recommendation on Tmall, RetailRocket, and IJCAI.
Improvedrecurrentneuralnetworks forsession-basedrecommendations,in:Proceedingsofthe1stWork- shop on Deep Learning for Recommender Systems
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PHKT:Personalized Dynamic Hypergraph-enhanced KAN-Transformer for Multi-behavior Sequential Recommendation
PHKT uses personalized dynamic hypergraphs and KAN-Transformer to outperform baselines in multi-behavior sequential recommendation on Tmall, RetailRocket, and IJCAI.