1 |
刘华锋,景丽萍,于剑. 融合社交信息的矩阵分解推荐方法研究综述[J]. 软件学报, 2018, 29(2):340-362. 10.13328/j.cnki.jos.005391
|
|
LIU H F, JING L P, YU J. Survey of matrix factorization based recommendation methods by integrating social information[J]. Journal of Software, 2018, 29(2): 340-362. 10.13328/j.cnki.jos.005391
|
2 |
LIU L, DU X, ZHU L, et al. Learning discrete hashing towards efficient fashion recommendation[J]. Data Science and Engineering, 2018, 3(4):307-322. 10.1007/s41019-018-0079-z
|
3 |
GAO D, TONG Y, SHE J, et al. Top-k team recommendation and its variants in spatial crowdsourcing[J]. Data Science and Engineering, 2017, 2(2): 136-150. 10.1007/s41019-017-0037-1
|
4 |
WANG C D, DENG Z H, LAI J H, et al. Serendipitous recommendation in e-commerce using innovator-based collaborative filtering[J]. IEEE Transactions on Cybernetics, 2019, 49(7): 2678-2692. 10.1109/tcyb.2018.2841924
|
5 |
SRIVASTAVA R, PALSHIKAR G K, CHAURASIA S, et al. What’s next? A recommendation system for industrial training[J]. Data Science and Engineering, 2018, 3(3): 232-247. 10.1007/s41019-018-0076-2
|
6 |
ADOMAVICIUS G, TUZHILIN A. Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions[J]. IEEE Transactions on Knowledge and Data Engineering, 2005, 17(6): 734-749. 10.1109/tkde.2005.99
|
7 |
BREESE J S, HECKERMAN D, KADIE C. Empirical analysis of predictive algorithms for collaborative filtering[C]// Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence. San Francisco: Morgan Kaufmann Publishers Inc., 1998: 43-52.
|
8 |
WANG J, DE VRIES A P, REINDERS M J T. Unifying user-based and item-based collaborative filtering approaches by similarity fusion[C]// Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. New York: ACM, 2006: 501-508. 10.1145/1148170.1148257
|
9 |
郭兰杰,梁吉业,赵兴旺. 融合社交网络信息的协同过滤推荐算法[J]. 模式识别与人工智能, 2016, 29(3):281-288. 10.16451/j.cnki.issn1003-6059.201603010
|
|
GUO L J, LIANG J Y, ZHAO X W. Collaborative filtering recommendation algorithm incorporating social network information[J]. Pattern Recognition and Artificial Intelligence, 2016, 29(3): 281-288. 10.16451/j.cnki.issn1003-6059.201603010
|
10 |
张俊,刘满,彭维平,等. 融合兴趣和评分的协同过滤推荐算法[J]. 小型微型计算机系统, 2017, 38(2):357-362.
|
|
ZHANG J, LIU M, PENG W P, et al. Collaborative filtering recommendation algorithm based on fusion interest and score[J]. Journal of Chinese Computer Systems, 2017, 38(2):357-362.
|
11 |
TAHERI S M, MAHYAR H, FIROUZI M, et al. Extracting implicit social relation for social recommendation techniques in user rating prediction[C]// Proceedings of the 26th International Conference on World Wide Web Companion. Republic and Canton of Geneva: International World Wide Web Conferences Steering Committee, 2017: 1343-1351. 10.1145/3041021.3051153
|
12 |
SONG K, GAO W, SHI F, et al. Recommendation vs sentiment analysis: a text-driven latent factor model for rating prediction with cold-start awareness[C]// Proceedings of the 26th International Joint Conference on Artificial Intelligence. California: ijcai.org, 2017: 2744-2750. 10.24963/ijcai.2017/382
|
13 |
LI Y, LIU J, REN J, et al. A novel implicit trust recommendation approach for rating prediction[J]. IEEE Access, 2020, 8:98305-98315. 10.1109/access.2020.2997040
|
14 |
CHEN H, SUN H, CHENG M, et al. A recommendation approach for rating prediction based on user interest and trust value[J]. Computational Intelligence and Neuroscience, 2021, 2021: No.6677920. 10.1155/2021/6677920
|
15 |
PURKAYSTHA B, DATTA T, ISLAM M S, et al. Rating prediction for recommendation: constructing user profiles and item characteristics using backpropagation[J]. Applied Soft Computing, 2019, 75:310-322. 10.1016/j.asoc.2018.11.018
|
16 |
TANG J, ZHANG X, ZHANG M, et al. A neural joint model for rating prediction recommendation[J]. Journal of Computational Methods in Sciences and Engineering, 2020, 20(4):1127-1142. 10.3233/jcm-204226
|
17 |
JI S, YANG W, GUO S, et al. Asymmetric response aggregation heuristics for rating prediction and recommendation[J]. Applied Intelligence, 2020, 50(5): 1416-1436. 10.1007/s10489-019-01594-2
|
18 |
YANG Z, ZHANG M. TextOG: a recommendation model for rating prediction based on heterogeneous fusion of review data[J]. IEEE Access, 2020, 8: 159566-159573. 10.1109/access.2020.3020942
|
19 |
ZHOU D, HAO S, ZHANG H, et al. Novel SDDM rating prediction models for recommendation systems[J]. IEEE Access, 2021, 9: 101197-101206. 10.1109/access.2021.3097207
|
20 |
朵琳,杨丙. 一种基于用户兴趣概念格的推荐评分预测方法[J]. 小型微型计算机系统, 2020, 41(10): 2104-2108. 10.3969/j.issn.1000-1220.2020.10.014
|
|
DUO L, YANG B. Recommendation rating prediction based on user interest concept lattice[J]. Journal of Chinese Computer Systems, 2020, 41(10): 2104-2108. 10.3969/j.issn.1000-1220.2020.10.014
|