Nanyang Technological University, Singapore
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Cited by
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Recurrent knowledge graph embedding for effective recommendation
Z Sun, J Yang, J Zhang, A Bozzon, LK Huang, C Xu
Proceedings of the 12th ACM conference on recommender systems, 297-305, 2018
Librec: A java library for recommender systems
G Guo, J Zhang, Z Sun, N Yorke-Smith
CEUR Workshop Proceedings 1388, 2015
Research commentary on recommendations with side information: A survey and research directions
Z Sun, Q Guo, J Yang, H Fang, G Guo, J Zhang, R Burke
Electronic Commerce Research and Applications 37, 100879, 2019
Are we evaluating rigorously? benchmarking recommendation for reproducible evaluation and fair comparison
Z Sun, D Yu, H Fang, J Yang, X Qu, J Zhang, C Geng
Proceedings of the 14th ACM Conference on Recommender Systems, 23-32, 2020
An attentional recurrent neural network for personalized next location recommendation
Q Guo, Z Sun, J Zhang, YL Theng
Proceedings of the AAAI Conference on artificial intelligence 34 (01), 83-90, 2020
Hierarchical attentive knowledge graph embedding for personalized recommendation
X Sha, Z Sun, J Zhang
Electronic Commerce Research and Applications 48, 101071, 2021
BPRH: Bayesian personalized ranking for heterogeneous implicit feedback
H Qiu, Y Liu, G Guo, Z Sun, J Zhang, HT Nguyen
Information Sciences 453, 80-98, 2018
Interacting attention-gated recurrent networks for recommendation
W Pei, J Yang, Z Sun, J Zhang, A Bozzon, DMJ Tax
Proceedings of the 2017 ACM on Conference on Information and Knowledge …, 2017
An Interactive Multi-Task Learning Framework for Next POI Recommendation with Uncertain Check-ins
L Zhang, Z Sun, J Zhang, Y Lei, C Li, Z Wu, H Kloeden, F Klanner
IJCAI 301 (985), 13954, 2020
Modeling hierarchical category transition for next POI recommendation with uncertain check-ins
L Zhang, Z Sun, J Zhang, H Kloeden, F Klanner
Information Sciences 515, 169-190, 2020
Minimalistic attacks: How little it takes to fool deep reinforcement learning policies
X Qu, Z Sun, YS Ong, A Gupta, P Wei
IEEE Transactions on Cognitive and Developmental Systems 13 (4), 806-817, 2020
Learning hierarchical feature influence for recommendation by recursive regularization
J Yang, Z Sun, A Bozzon, J Zhang
Proceedings of the 10th ACM Conference on Recommender Systems, 51-58, 2016
MRLR: Multi-level Representation Learning for Personalized Ranking in Recommendation.
Z Sun, J Yang, J Zhang, A Bozzon, Y Chen, C Xu
IJCAI, 2807-2813, 2017
Exploiting both vertical and horizontal dimensions of feature hierarchy for effective recommendation
Z Sun, J Yang, J Zhang, A Bozzon
Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017
Revisiting bundle recommendation: Datasets, tasks, challenges and opportunities for intent-aware product bundling
Z Sun, J Yang, K Feng, H Fang, X Qu, YS Ong
Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022
Next Point-of-Interest Recommendation with Inferring Multi-step Future Preferences
L Zhang, Z Sun, Z Wu, J Zhang, YS Ong, X Qu
IJCAI, 2022
Aspect-aware point-of-interest recommendation with geo-social influence
Q Guo, Z Sun, J Zhang, Q Chen, YL Theng
Adjunct Publication of the 25th Conference on User Modeling, Adaptation and …, 2017
Exploiting implicit item relationships for recommender systems
Z Sun, G Guo, J Zhang
User Modeling, Adaptation and Personalization: 23rd International Conference …, 2015
Does Every Data Instance Matter? Enhancing Sequential Recommendation by Eliminating Unreliable Data.
Y Sun, B Wang, Z Sun, X Yang
IJCAI, 1579-1585, 2021
Daisyrec 2.0: Benchmarking recommendation for rigorous evaluation
Z Sun, H Fang, J Yang, X Qu, H Liu, D Yu, YS Ong, J Zhang
IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (7), 8206-8226, 2022
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