Stebėti
Hui Fang
Pavadinimas
Cituota
Cituota
Metai
Topicmf: Simultaneously exploiting ratings and reviews for recommendation
Y Bao, H Fang, J Zhang
Proceedings of the AAAI Conference on Artificial Intelligence 28 (1), 2014
3742014
Deep learning for sequential recommendation: Algorithms, influential factors, and evaluations
H Fang, D Zhang, Y Shu, G Guo
ACM Transactions on Information Systems (TOIS) 39 (1), 1-42, 2020
3082020
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
2262019
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
1812020
Towards effective online review systems in the Chinese context: A cross-cultural empirical study
H Fang, J Zhang, Y Bao, Q Zhu
Electronic Commerce Research and Applications 12 (3), 208-220, 2013
1322013
Leveraging decomposed trust in probabilistic matrix factorization for effective recommendation
H Fang, Y Bao, J Zhang
AAAI 2014, 2014
1202014
Multi-faceted trust and distrust prediction for recommender systems
H Fang, G Guo, J Zhang
Decision Support Systems 71, 37-47, 2015
972015
A blockchain-based scheme for secure data offloading in healthcare with deep reinforcement learning
Q He, Z Feng, H Fang, X Wang, L Zhao, Y Yao, K Yu
IEEE/ACM Transactions on Networking 32 (1), 65-80, 2023
852023
Dynamic opinion maximization in social networks
Q He, H Fang, J Zhang, X Wang
IEEE Transactions on Knowledge and Data Engineering 35 (1), 350-361, 2021
692021
Deep learning-based sequential recommender systems: Concepts, algorithms, and evaluations
H Fang, G Guo, D Zhang, Y Shu
Web Engineering: 19th International Conference, ICWE 2019, Daejeon, South …, 2019
642019
Reputation mechanism for e-commerce in virtual reality environments
H Fang, J Zhang, M Şensoy, N Magnenat-Thalmann
Electronic Commerce Research and Applications 13 (6), 409-422, 2014
502014
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
362022
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
352022
Intrank: Interaction ranking-based trustworthy friend recommendation
L Zhang, H Fang, WK Ng, J Zhang
2011IEEE 10th International Conference on Trust, Security and Privacy in …, 2011
352011
Multistage Competitive Opinion Maximization With Q-Learning-Based Method in Social Networks
Q He, L Zhang, H Fang, X Wang, L Ma, K Yu, J Zhang
IEEE Transactions on Neural Networks and Learning Systems, 2024
342024
A trust model stemmed from the diffusion theory for opinion evaluation
H Fang, J Zhang, NM Thalmann
Proceedings of the 2013 international conference on autonomous agents and …, 2013
332013
A generalized stereotypical trust model
H Fang, J Zhang, M Sensoy, NM Thalmann
2012 IEEE 11th International Conference on Trust, Security and Privacy in …, 2012
312012
SARC: subjectivity alignment for reputation computation.
H Fang, J Zhang, M Sensoy, N Magnenat-Thalmann
AAMAS, 1365-1366, 2012
282012
Rethinking the Link Prediction Problem in Signed Social Networks
X Li, H Fang, J Zhang
The Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), 2017
242017
Subjectivity grouping: Learning from users' rating behavior
H Fang, J Zhang, N Magnenat Thalmann
Proceedings of the 2014 international conference on autonomous agents and …, 2014
222014
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