第1期 王健宗，等：联邦推荐系统的协同过滤冷启动解决方法 ·185· scheme[D].Palo Alto:Stanford University,2009 history and context[J].ACM transactions on interactive [28]CANNY J.Collaborative filtering with privacy via factor intelligent systems,2015,5(4):19. analysis[C]//Proceedings of the 25th Annual International [36]KOREN Y.Factorization meets the neighborhood:a mul- ACM SIGIR Conference on Research and Development tifaceted collaborative filtering model[Cl//Proceedings of in Information Retrieval.Tampere,Finland,2002: the 14th ACM SIGKDD International Conference on 238-245 Knowledge Discovery and Data Mining.Nevada,Las Ve- [29]CHEN Chaochao,ZHOU Jun,WU Bingzhe,et al.Prac- gas,USA,2008:426-434. tical privacy preserving POI recommendation[J].ACM [37]NIKOLAENKO V,WEINSBERG U,IOANNIDIS S,et transactions on intelligent systems and technology,2020, 11(5):52. al.Privacy-preserving ridge regression on hundreds of [30]CHEN Chaochao,LIU Ziqi,ZHAO Peilin,et al.Privacy millions of records[Cl//Proceedings of 2013 IEEE Sym- preserving point-of-interest recommendation using de- posium on Security and Privacy.Berkeley,USA,2013: centralized matrix factorization[C]//Proceedings of the 334348. 32nd AAAI Conference on Artificial Intelligence.New 作者简介： Orleans,Louisiana,USA,2018:257-264. 王健宗，高级工程师，博土，主要 [31]ERKIN Z,BEYE M,VEUGEN T,et al.Efficiently com- 研究方向为联邦学习算法、金融智能 puting private recommendations[Cl//Proceedings of 2011 平台。主持国家重点研发计划基金项 IEEE International Conference on Acoustics,Speech and 目3项、校企联合课题2项，授权发明 Signal Processing.Prague,Czech Republic,2011: 专利100余项。发表学术论文50余 5864-5867. 篇，出版著作3部。 [32]KATARYA R,VERMA O P.Effective collaborative movie recommender system using asymmetric user simil- 肖京，教授级高级工程师，博士， arity and matrix factorization[Cl//Proceedings of 2016 In- 主要研究方向为人工智能与大数据分 ternational Conference on Computing,Communication 析挖掘。国际授权专利101项，授权 and Automation.Noida.India.2016:71-75. 国内发明专利109项。2019年吴文俊 [33]HERLOCKER JL,KONSTAN J A,BORCHERS A,et 人工智能科学技术奖“杰出贡献奖”获 al.An algorithmic framework for performing collaborat- 得者，发表学术论文130余篇。 ive filtering[C]//Proceedings of the 22nd Annual Interna- tional ACM SIGIR Conference on Research and Develop- ment in Information Retrieval.California,Berkeley, 朱星华，博士研究生，主要研究方 向为联邦学习、机器视觉算法。 USA,1999:230-237. [34]GASCON A,SCHOPPMANN P,BALLE B,et al.Se- cure linear regression on vertically partitioned datasets[J]. IACR cryptology ePrint archive,2016,2016:892. [35]HARPER F M.KONSTAN J A.The movielens datasets:scheme[D]. Palo Alto: Stanford University, 2009. CANNY J. Collaborative filtering with privacy via factor analysis[C]//Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Tampere, Finland, 2002: 238–245. [28] CHEN Chaochao, ZHOU Jun, WU Bingzhe, et al. Prac￾tical privacy preserving POI recommendation[J]. ACM transactions on intelligent systems and technology, 2020, 11(5): 52. [29] CHEN Chaochao, LIU Ziqi, ZHAO Peilin, et al. Privacy preserving point-of-interest recommendation using de￾centralized matrix factorization[C]//Proceedings of the 32nd AAAI Conference on Artificial Intelligence. New Orleans, Louisiana, USA, 2018: 257–264. [30] ERKIN Z, BEYE M, VEUGEN T, et al. Efficiently com￾puting private recommendations[C]//Proceedings of 2011 IEEE International Conference on Acoustics, Speech and Signal Processing. Prague, Czech Republic, 2011: 5864–5867. [31] KATARYA R, VERMA O P. Effective collaborative movie recommender system using asymmetric user simil￾arity and matrix factorization[C]//Proceedings of 2016 In￾ternational Conference on Computing, Communication and Automation. Noida, India, 2016: 71–75. [32] HERLOCKER J L, KONSTAN J A, BORCHERS A, et al. An algorithmic framework for performing collaborat￾ive filtering[C]//Proceedings of the 22nd Annual Interna￾tional ACM SIGIR Conference on Research and Develop￾ment in Information Retrieval. California, Berkeley, USA, 1999: 230–237. [33] GASCON A, SCHOPPMANN P, BALLE B, et al. Se￾cure linear regression on vertically partitioned datasets[J]. IACR cryptology ePrint archive, 2016, 2016: 892. [34] [35] HARPER F M, KONSTAN J A. The movielens datasets: history and context[J]. ACM transactions on interactive intelligent systems, 2015, 5(4): 19. KOREN Y. Factorization meets the neighborhood: a mul￾tifaceted collaborative filtering model[C]//Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Nevada, Las Ve￾gas, USA, 2008: 426–434. [36] NIKOLAENKO V, WEINSBERG U, IOANNIDIS S, et al. Privacy-preserving ridge regression on hundreds of millions of records[C]//Proceedings of 2013 IEEE Sym￾posium on Security and Privacy. Berkeley, USA, 2013: 334–348. [37] 作者简介： 王健宗，高级工程师，博士，主要 研究方向为联邦学习算法、金融智能 平台。主持国家重点研发计划基金项 目 3 项、校企联合课题 2 项，授权发明 专利 100 余项。发表学术论文 50 余 篇，出版著作 3 部。 肖京，教授级高级工程师，博士， 主要研究方向为人工智能与大数据分 析挖掘。国际授权专利 101 项，授权 国内发明专利 109 项。2019 年吴文俊 人工智能科学技术奖“杰出贡献奖”获 得者，发表学术论文 130 余篇。 朱星华，博士研究生，主要研究方 向为联邦学习、机器视觉算法。 第 1 期 王健宗，等：联邦推荐系统的协同过滤冷启动解决方法 ·185·