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20222026
most citedTowards Semi-supervised Universal Graph Classification

47 citations · 168 across the 33 of their papers we have counts for

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5 papers · 1 filter

cs.IR2026

Interests Burn-down Diffusion Process for Personalized Collaborative Filtering

Yifang Qin, Zhaobin Li, Arisa Watanabe +3

Generative methods have gained widespread attention in Collaborative Filtering (CF) tasks for their ability to produce high-quality personalized samples aligned with users' interes…

cs.IR20245 cited

DisCo: Graph-Based Disentangled Contrastive Learning for Cold-Start Cross-Domain Recommendation

Hourun Li, Yifan Wang, Zhiping Xiao +4

Recommender systems are widely used in various real-world applications, but they often encounter the persistent challenge of the user cold-start problem. Cross-domain recommendatio…

cs.IR2024

PolyCF: Towards the Optimal Spectral Graph Filters for Collaborative Filtering

Yifang Qin, Wei Ju, Xiao Luo +3

Collaborative Filtering (CF) is a pivotal research area in recommender systems that capitalizes on collaborative similarities between users and items to provide personalized recomm…

cs.IR2023

Learning Graph ODE for Continuous-Time Sequential Recommendation

Yifang Qin, Wei Ju, Hongjun Wu +2

Sequential recommendation aims at understanding user preference by capturing successive behavior correlations, which are usually represented as the item purchasing sequences based…

cs.IR2023

A Diffusion model for POI recommendation

Yifang Qin, Hongjun Wu, Wei Ju +2

Next Point-of-Interest (POI) recommendation is a critical task in location-based services that aim to provide personalized suggestions for the user's next destination. Previous wor…