Computer Science ›› 2021, Vol. 48 ›› Issue (1): 226-232.doi: 10.11896/jsjkx.191200098
• Artificial Intelligence • Previous Articles Next Articles
WANG Rui-ping, JIA Zhen, LIU Chang, CHEN Ze-wei, LI Tian-rui
CLC Number:
[1] MARZ N,WARREN J.Big Data:Principles and best practices of scalable realtime data systems[M].Manning Publications,2015. [2] RICCI F,ROKACH L,SHAPIRA B.Introduction to Recom-mender Systems Handbook[M]//Recommender Systems Handbook.Boston:Springer,2011:1-35. [3] YU C J,ZHUANG Y,WEI S C,et al.Field-aware factorization machines for CTR prediction[C]//Proceedings of the 10th ACM Conference on Recommender Systems.ACM,2016:43-50. [4] COVINGTON P,ADAMS J,SARGIN E.Deep neural networks for youtube recommendations[C]//Proceedings of the 10th ACM Conference on Recommender Systems.ACM,2016:191-198. [5] ZHOU G R,ZHU X Q,SONG C R,et al.Deep interest network for click-through rate prediction[C]//Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining.ACM,2018:1059-1068. [6] CHEN Q,ZHAO H,LI W,et al.Behavior Sequence Transformer for E-commerce Recommendation in Alibaba[J].arXiv:1905.06874,2019. [7] ZHOU G R,MOU N,FAN Y,et al.Deep interest evolution network for click-through rate prediction[C]//Proceedings of the AAAI Conference on Artificial Intelligence.2019:5941-5948. [8] CHENG H T,KOC L,HARMSEN J,et al.Wide & deep learning for recommender systems[C]//Proceedings of the 1st Workshop on Deep Learning for Recommender Systems.ACM,2016:7-10. [9] GUO H F,TANG R M,YE Y M,et al.DeepFM:a factorization-machine based neural network for CTR prediction[C]//Proceedings of the 26th International Joint Conference on Artificial Intelligence.AAAI Press,2017:1725-1731. [10] RENDLE S.Factorization machines[C]//Proceedings of 2010 IEEE International Conference on Data Mining.IEEE,2010:995-1000. [11] VASWANI A,SHAZEER N,PARMAR N,et al.Attention isall you need[C]//Advances in Neural Information Processing Systems.2017:5998-6008. [12] MCAULEY J,TARGETT C,SHI Q,et al.Image-based recommendations on styles and substitutes[C]//Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval.ACM,2015:43-52. [13] HE R,MCAULEY J.Ups and downs:Modeling the visual evolution of fashion trends with one-class collaborative filtering[C]//Proceedings of the 25th International Conference on World Wide Web.2016:507-517. [14] HARPER F M,KONSTAN J A.The movielens datasets:His-tory and context[J].ACM Transactions on Interactive Intelligent Systems,2015,5(4):19. [15] QU Y,CAI H,REN K,et al.Product-based neural networks for user response prediction[C]//Proceedings of 2016 IEEE 16th International Conference on Data Mining.2016:1149-1154. [16] ZHU H,JIN J,TAN C,et al.Optimized cost per click in taobao display advertising[C]//Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.ACM:2191-2200. [17] YAN L,LI W J,XUE G R,et al.Coupled group lasso for web-scale ctr prediction in display advertising[C]//Proceedings of International Conference on Machine Learning.2014:802-810. [18] RICHARDSON M,DOMINOWSKA E,RAGNO R.Predicting clicks:estimating the click-through rate for new ads[C]//Proceedings of the 16th International Conference on World Wide Web.ACM,2007:521-530. [19] FENG YF,LV F Y,SHEN W C,et al.Deep session interest network for click-through rate prediction[C]//Proceedings of 28th International Joint Conference on Artificial Intelligence.2019. [20] ZHU H,LI X,ZhANG P,et al.Learning tree-based deep model for recommender systems[C]//Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining.2018:1079-1088. |
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