[1] |
Sarwar B,Karypis G,Konstan J,et al.Item-based collaborative filtering recommendation algorithms[C]∥Proc of the 10th International Conference on World Wide Web,2001:285-295.
|
[2] |
Koren Y,Bell R,Volinsky C.Matrix factorization techniques for recommender systems[J].Computer,2009,42(8):30-37.
|
[3] |
Mnih A,Salakhutdinov R R.Probabilistic matrix factorization[C]∥Proc of the 20th International Conference on Neural Information Processing Systems,2007:1257-1264.
|
[4] |
Zhang Yan-ping,Zhang Shun,Qian Fu-lan,et al.Robust collaborative recommendation algorithm based on users reputation[J].Acta Automatica Sinica,2015,41(5):1004-1012.(in Chinese)
|
[5] |
Cheng Ying-chao, Wang Rui-hu,Hu Zhang-ping.Novel approach on collaborative filtering based on Gaussian mixture model[J].Computer Science,2017,44(Z6):451-454.(in Chinese)
|
[6] |
Jia Jun-jie, Yao Ye-wang,Chen Wang-hu.A group recommendation algorithm based on non-negative matrix factorization[J].Computer Engineering & Science,2022,44(5):933-943.(in Chinese)
|
[7] |
Ahmadian S,Afsharchi M,Meghdadi M.An effective social recommendation method based on user reputation model and rating profile enhancement[J].Journal of Information Science,2019,45(5):607-642.
|
[8] |
Liu X,Ouyang Y,Rong W,et al.Item category aware conditional restricted boltzmann machine based recommendation[C]∥Proc of the International Conference on Neural Information Processing,2015:609-616.
|
[9] |
Zhuang F,Zhang Z,Qian M,et al.Representation learning via dual-autoencoder for recommendation[J].Neural Networks,2017,90(1):83-89.
|
[10] |
Yang Feng-rui,Li Qian-yang,Luo Si-fan.An implicit feedback recommendation algorithm based on denoising autoencoder[J].Computer Engineering & Science,2020,42(8):1500-1505.(in Chinese)
|
[11] |
Qian Fu-lan,Li Jian-hong,Zhao Shu,et al.Rating recommendation based on deep hybrid model[J].Journal of Nanjing University of Aeronautics & Astronautics,2019,51(5):592-598.(in Chinese)
|
[12] |
Cheng H T,Koc L,Harmsen J,et al.Wide & deep learning for recommender systems[C]∥Proc of the 1st Workshop on Deep Learning for Recommender Systems,2016:7-10.
|
[13] |
Dawen L,Rahul G,Mathew D,et al.Vrational autoencoders for collaborative filtering[C]∥Proc of the 2018 Worid Wide Web Conference,2018:689-698.
|
[14] |
Lü Y X,Zheng Y,Wei F N,et al.AICF:Attention-based item collaborative filtering[J].Advanced Engineering Informatics,2020,44:101090.
|
[15] |
Pang G Y,Wang X M,Hao F,et al.ACNN-FM:A novel recommender with attention-based convolutional neural network and factorization machines[J].Knowledge-Based Systems,2019,181:104786.
|
[16] |
Wang Y X,Zhang Y J.Nonnegative matrix factorization:A comprehensive review[J].IEEE Transactions on Know- ledge and Data Engineering,2012,25(6):1336-1353.
|
[17] |
Sabetsarvestani Z,Kiraly F,Miguel R,et al.Entry-wise matrix completion from noisy entries[C]∥Proc of the 26th European Signal Processing Conference,2018:2603-2607.
|
[18] |
Jia Y,Wang X,Zhang J.Collaborative filtering via learning characteristics of neighborhood based on convolutional neural networks[C]∥Proc of the Workshop on Deep Learning Practice for High-Dimensional Sparse Data,2019:1-4.
|
[19] |
Xue H J,Dai X,Zhang J,et al.Deep matrix factorization models for recommender systems[C]∥Proc of the 40th International Joint Conference on Artificial Intelligence,2017:3203-3209.
|
[20] |
Li P,Wang Z,Ren Z,et al.Neural rating regression with abstractive tips generation for recommendation[C]∥Proc of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval,2017:345-354.
|
[21] |
Qian F,Huang Y,Li J,et al.DLSA:Dual-learning based on self-attention for rating prediction[J].International Journal of Machine Learning and Cybernetics,2021,12(7):1993-2005.
|
[22] |
Nguyen M, Tsiligianni E, Deligiannis N.Extendable neural matrix completion[C]∥Proc of IEEE International Confe- rence on Acoustics, Speech and Signal Processing, 2018: 6328-6332.
|
[23] |
Chen H,Qian F,Chen J,et al.Attribute-based neural collabor ative filtering[J].Expert Systems with Applications,2021,185(1):115539.
|
[24] |
Chen H,Qian F L,Chen J,et al.FG-RS:Capture user fine-grained preferences through attribute information for Recommender Systems[J].Neurocomputing,2021,458:195-203.
|
[25] |
Chen J, Wang X S,Zhao S,et al.Attention user-based collaborative filtering for recommendation[J].Neurocomputing,2020,383:57-68.
|
[26] |
Liu W,Zheng X,Hu M,et al.Collaborative filtering with attribution alignment for review-based non-overlapped cross domain recommendation[C]∥Proc of the ACM Web Conference,2022:1181-1190.
|
[27] |
Afchar D,Hennequin R.Making neural networks interpretable with attribution:Application to implicit signals prediction[C]∥Proc of the 14th ACM Conference on Recommender Systems,2020:220-229.
|
[28] |
Dellal B,Alimazighi Z.Hybrid filtering and semantic sentiment analysis by deep learning for recommendation systems[J].International Journal of Information Science and Technology,2022,6(3):16-28.
|
[29] |
Dellal-Hedjazi B,Alimazighi Z.Deep learning for recommendation systems[C]∥Proc of the 6th IEEE Congress on Information Science and Technology,2021:90-97.
|
[30] |
Wu Z,Pan S,Chen F,et al.A comprehensive survey on graph neural networks[J].IEEE Transactions on Neural Networks and Learning Systems,2020,32(1):4-24.
|
[31] |
Fan W,Ma Y,Li Q,et al.Graph neural networks for social recommendation[C]∥Proc of the World Wide Web Confe- rence,2019:417-426.
|
[32] |
Li S S,Yang B,Li D S.Entity-driven user intent inference for knowledge graph-based recommendation[J].Applied Intelligence,2022:1-17.DOI:10.1007/s10489-022-04048-4.
|
[33] |
Monti F,Bronstein M,Bresson X.Geometric matrix completion with recurrent multi-graph neural networks[C]∥Proc of the 31st International Conference on Neural Information Processing Systems,2017:3700-3710.
|
[34] |
Zhang M,Chen Y.Inductive graph pattern learning for recommender systems based on a graph neural network[J].arXiv:1904.12058,2019.
|
[35] |
Huang Li-wei,Jiang Bi-tao,Lü Shou-ye,et al.Survey of recommender systems based on deep learning[J].Chinese Journal of Computers,2018,41(7):1619-1647.(in Chinese)
|
[36] |
Lee M,Lee J,Lee D,et al.Robust lane detection via expanded self-attention[C]∥Proc of the IEEE/CVF Winter Conference on Applications of Computer Vision,2022:533-542.
|
[37] |
Ma H,Zhou D,Liu C,et al.Recommender systems with social regularization[C]∥Proc of the 4th ACM International Conference on Web Search and Data Mining,2011:287-296.
|
[38] |
Anand R,Beel J.Auto-surprise:An automated recommender- system (autorecsys) library with tree of parzens estimator (tpe) optimization[C]∥Proc of the 14th ACM Conference on Recommender Systems,2020:585-587.
|
[39] |
Liang H,Baldwin T.A probabilistic rating auto-encoder for personalized recommender systems[C]∥Proc of the 24th ACM International Conference on Information and Knowledge Management,2015:1863-1866.
|
[40] |
Locatello F,Yurtsever A,Fercoq O,et al.Stochastic frank-wolfe for composite convex minimization[C]∥Proc of the 33rd International Conference on Neural Information Processing Systems,2019:14291-14301.
|
[41] |
Fadel S G,Torres R S.Link prediction in dynamic graphs for recommendation[J].arXiv:1811.07174,2018.
|
|
附中文参考文献:
|
[4] |
张燕平,张顺,钱付兰,等.基于用户声誉的鲁棒协同推荐算法[J].自动化学报,2015,41(5):1004-1012.
|
[5] |
成英超,王瑞胡,胡章平.一种基于高斯混合模型的协同过滤算法[J].计算机科学,2017,44(Z6):451-454.
|
[6] |
贾俊杰,姚叶旺,陈旺虎.基于非负矩阵分解的群组推荐算法[J].计算机工程与科学,2022,44(5):933-943.
|
[10] |
杨丰瑞,李前洋,罗思烦.一种基于降噪自编码器的隐式反馈推荐算法[J].计算机工程与科学,2020,42(8):1500-1505.
|
[11] |
钱付兰,李建红,赵姝,等.基于深度混合模型评分推荐 [J].南京航空航天大学学报,2019,51(5):592-598.
|
[35] |
黄立威,江碧涛,吕守业,等.基于深度学习的推荐系统研究综述[J].计算机学报,2018,41(7):1619-1647.
|