most citedHeterogeneous Global Graph Neural Networks for Personalized Session-based Recommendation

142 citations · 153 across the 6 of their papers we have counts for

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5 papers · 1 filter

cs.IR2021★ 7 cited

Temporal aware Multi-Interest Graph Neural Network For Session-based Recommendation

Qi Shen, Shixuan Zhu, Yitong Pang +2

Session-based recommendation (SBR) is a challenging task, which aims at recommending next items based on anonymous interaction sequences. Despite the superior performance of existi…

cs.IR2021

Intention Adaptive Graph Neural Network for Category-aware Session-based Recommendation

Chuan Cui, Qi Shen, Shixuan Zhu +4

Session-based recommendation (SBR) is proposed to recommend items within short sessions given that user profiles are invisible in various scenarios nowadays, such as e-commerce and…

cs.IR2021★ 2 cited

Multi-behavior Graph Contextual Aware Network for Session-based Recommendation

Qi Shen, Lingfei Wu, Yitong Pang +4

Predicting the next interaction of a short-term sequence is a challenging task in session-based recommendation (SBR).Multi-behavior session recommendation considers session sequenc…

cs.IR2021★ 2 cited

Graph Learning Augmented Heterogeneous Graph Neural Network for Social Recommendation

Yiming Zhang, Lingfei Wu, Qi Shen +5

Social recommendation based on social network has achieved great success in improving the performance of recommendation system. Since social network (user-user relations) and user-…

cs.IR2021★ 142 cited

Heterogeneous Global Graph Neural Networks for Personalized Session-based Recommendation

Yitong Pang, Lingfei Wu, Qi Shen +6

Predicting the next interaction of a short-term interaction session is a challenging task in session-based recommendation. Almost all existing works rely on item transition pattern…