{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T03:31:53Z","timestamp":1772595113302,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":32,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,8,20]],"date-time":"2020-08-20T00:00:00Z","timestamp":1597881600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,8,23]]},"DOI":"10.1145\/3394486.3403341","type":"proceedings-article","created":{"date-parts":[[2020,8,20]],"date-time":"2020-08-20T23:03:55Z","timestamp":1597964635000},"page":"2900-2908","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":13,"title":["Improving Recommendation Quality in Google Drive"],"prefix":"10.1145","author":[{"given":"Suming J.","family":"Chen","sequence":"first","affiliation":[{"name":"Google LLC, Los Angeles, CA, USA"}]},{"given":"Zhen","family":"Qin","sequence":"additional","affiliation":[{"name":"Google LLC, Mountain View, CA, USA"}]},{"given":"Zac","family":"Wilson","sequence":"additional","affiliation":[{"name":"Google LLC, Boulder, CO, USA"}]},{"given":"Brian","family":"Calaci","sequence":"additional","affiliation":[{"name":"Google LLC, Boulder, CO, USA"}]},{"given":"Michael","family":"Rose","sequence":"additional","affiliation":[{"name":"Google LLC, Boulder, CO, USA"}]},{"given":"Ryan","family":"Evans","sequence":"additional","affiliation":[{"name":"Google LLC, Boulder, CO, USA"}]},{"given":"Sean","family":"Abraham","sequence":"additional","affiliation":[{"name":"Google LLC, Boulder, CO, USA"}]},{"given":"Donald","family":"Metzler","sequence":"additional","affiliation":[{"name":"Google LLC, Mountain View, CA, USA"}]},{"given":"Sandeep","family":"Tata","sequence":"additional","affiliation":[{"name":"Google LLC, Mountain View, CA, USA"}]},{"given":"Michael","family":"Colagrosso","sequence":"additional","affiliation":[{"name":"Google LLC, Boulder, CA, USA"}]}],"member":"320","published-online":{"date-parts":[[2020,8,20]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Mart\u00edn Abadi Ashish Agarwal Paul Barham Eugene Brevdo Zhifeng Chen Craig Citro Greg S. Corrado Andy Davis Jeffrey Dean Matthieu Devin Sanjay Ghemawat Ian Goodfellow Andrew Harp Geoffrey Irving Michael Isard Yangqing Jia Rafal Jozefowicz Lukasz Kaiser Manjunath Kudlur Josh Levenberg Dan Man\u00e9 Rajat Monga Sherry Moore Derek Murray Chris Olah Mike Schuster Jonathon Shlens Benoit Steiner Ilya Sutskever Kunal Talwar Paul Tucker Vincent Vanhoucke Vijay Vasudevan Fernanda Vi\u00e9gas Oriol Vinyals Pete Warden Martin Wattenberg Martin Wicke Yuan Yu and Xiaoqiang Zheng 2015. TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems. http:\/\/tensorflow.org\/ Software available from tensorflow.org. Mart\u00edn Abadi Ashish Agarwal Paul Barham Eugene Brevdo Zhifeng Chen Craig Citro Greg S. Corrado Andy Davis Jeffrey Dean Matthieu Devin Sanjay Ghemawat Ian Goodfellow Andrew Harp Geoffrey Irving Michael Isard Yangqing Jia Rafal Jozefowicz Lukasz Kaiser Manjunath Kudlur Josh Levenberg Dan Man\u00e9 Rajat Monga Sherry Moore Derek Murray Chris Olah Mike Schuster Jonathon Shlens Benoit Steiner Ilya Sutskever Kunal Talwar Paul Tucker Vincent Vanhoucke Vijay Vasudevan Fernanda Vi\u00e9gas Oriol Vinyals Pete Warden Martin Wattenberg Martin Wicke Yuan Yu and Xiaoqiang Zheng 2015. TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems. http:\/\/tensorflow.org\/ Software available from tensorflow.org."},{"key":"e_1_3_2_1_2_1","volume-title":"RecSys 2014 Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS","author":"Adomavicius Gediminas","year":"2014","unstructured":"Gediminas Adomavicius , Jesse Bockstedt , Shawn Curley , and Jingjing Zhang . 2014 . De-biasing user preference ratings in recommender systems . In RecSys 2014 Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2014). 2--9. Gediminas Adomavicius, Jesse Bockstedt, Shawn Curley, and Jingjing Zhang. 2014. De-biasing user preference ratings in recommender systems. In RecSys 2014 Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2014). 2--9."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"crossref","unstructured":"Gediminas Adomavicius and Alexander Tuzhilin. 2008. Context-aware Recommender Systems. In RecSys. 335--336. Gediminas Adomavicius and Alexander Tuzhilin. 2008. Context-aware Recommender Systems. In RecSys. 335--336.","DOI":"10.1145\/1454008.1454068"},{"key":"e_1_3_2_1_4_1","unstructured":"Denis Baylor Eric Breck Heng-Tze Cheng Noah Fiedel Chuan Yu Foo Zakaria Haque Salem Haykal Mustafa Ispir Vihan Jain Levent Koc Chiu Yuen Koo Lukasz Lew Clemens Mewald Akshay Naresh Modi Neoklis Polyzotis Sukriti Ramesh Sudip Roy Steven Euijong Whang Martin Wicke Jarek Wilkiewicz Xin Zhang and Martin Zinkevich. 2017. TFX: A TensorFlow-Based Production-Scale Machine Learning Platform. In KDD. Denis Baylor Eric Breck Heng-Tze Cheng Noah Fiedel Chuan Yu Foo Zakaria Haque Salem Haykal Mustafa Ispir Vihan Jain Levent Koc Chiu Yuen Koo Lukasz Lew Clemens Mewald Akshay Naresh Modi Neoklis Polyzotis Sukriti Ramesh Sudip Roy Steven Euijong Whang Martin Wicke Jarek Wilkiewicz Xin Zhang and Martin Zinkevich. 2017. TFX: A TensorFlow-Based Production-Scale Machine Learning Platform. In KDD."},{"key":"e_1_3_2_1_5_1","volume-title":"Chi","author":"Beutel Alex","year":"2018","unstructured":"Alex Beutel , Paul Covington , Sagar Jain , Can Xu , Jia Li , Vince Gatto , and Ed H . Chi . 2018 . Latent Cross : Making Use of Context in Recurrent Recommender Systems. In WSDM. 46--54. Alex Beutel, Paul Covington, Sagar Jain, Can Xu, Jia Li, Vince Gatto, and Ed H. Chi. 2018. Latent Cross: Making Use of Context in Recurrent Recommender Systems. In WSDM. 46--54."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"crossref","unstructured":"Zhe Cao Tao Qin Tie-Yan Liu Ming-Feng Tsai and Hang Li. 2007. Learning to Rank: From Pairwise Approach to Listwise Approach. In ICML. 129--136. Zhe Cao Tao Qin Tie-Yan Liu Ming-Feng Tsai and Hang Li. 2007. Learning to Rank: From Pairwise Approach to Listwise Approach. In ICML. 129--136.","DOI":"10.1145\/1273496.1273513"},{"key":"e_1_3_2_1_7_1","volume-title":"Engelhardt","author":"Chaney Allison J. B.","year":"2018","unstructured":"Allison J. B. Chaney , Brandon M. Stewart , and Barbara E . Engelhardt . 2018 . How Algorithmic Confounding in Recommendation Systems Increases Homogeneity and Decreases Utility. In RecSys . 224--232. Allison J. B. Chaney, Brandon M. Stewart, and Barbara E. Engelhardt. 2018. How Algorithmic Confounding in Recommendation Systems Increases Homogeneity and Decreases Utility. In RecSys. 224--232."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371820"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/2988450.2988454"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"crossref","unstructured":"Paul Covington Jay Adams and Emre Sargin. 2016. Deep Neural Networks for YouTube Recommendations. In RecSys. Paul Covington Jay Adams and Emre Sargin. 2016. Deep Neural Networks for YouTube Recommendations. In RecSys.","DOI":"10.1145\/2959100.2959190"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/2988450.2988451"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"crossref","unstructured":"Tim Donkers Benedikt Loepp and J\u00fcrgen Ziegler. 2017. Sequential User-based Recurrent Neural Network Recommendations. In RecSys. 152--160. Tim Donkers Benedikt Loepp and J\u00fcrgen Ziegler. 2017. Sequential User-based Recurrent Neural Network Recommendations. In RecSys. 152--160.","DOI":"10.1145\/3109859.3109877"},{"key":"e_1_3_2_1_13_1","unstructured":"Elad Eban Mariano Schain Alan Mackey Ariel Gordon Ryan Rifkin and Gal Elidan. 2017. Scalable Learning of Non-Decomposable Objectives. In AISTATS. 832--840. Elad Eban Mariano Schain Alan Mackey Ariel Gordon Ryan Rifkin and Gal Elidan. 2017. Scalable Learning of Non-Decomposable Objectives. In AISTATS. 832--840."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"crossref","unstructured":"Simen Eide and Ning Zhou. 2018. Deep Neural Network Marketplace Recommenders in Online Experiments. In RecSys. 387--391. Simen Eide and Ning Zhou. 2018. Deep Neural Network Marketplace Recommenders in Online Experiments. In RecSys. 387--391.","DOI":"10.1145\/3240323.3240387"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098043"},{"key":"e_1_3_2_1_16_1","volume-title":"Applying Deep Learning To Airbnb Search. CoRR","author":"Haldar Malay","year":"2018","unstructured":"Malay Haldar , Mustafa Abdool , Prashant Ramanathan , Tao Xu , Shulin Yang , Huizhong Duan , Qing Zhang , Nick Barrow-Williams , Bradley C. Turnbull , Brendan M. Collins , and Thomas Legrand . 2018. Applying Deep Learning To Airbnb Search. CoRR , Vol. abs\/ 1810 .09591 ( 2018 ). arxiv: 1810.09591 http:\/\/arxiv.org\/abs\/1810.09591 Malay Haldar, Mustafa Abdool, Prashant Ramanathan, Tao Xu, Shulin Yang, Huizhong Duan, Qing Zhang, Nick Barrow-Williams, Bradley C. Turnbull, Brendan M. Collins, and Thomas Legrand. 2018. Applying Deep Learning To Airbnb Search. CoRR, Vol. abs\/1810.09591 (2018). arxiv: 1810.09591 http:\/\/arxiv.org\/abs\/1810.09591"},{"key":"e_1_3_2_1_17_1","unstructured":"Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016. Deep Residual Learning for Image Recognition. In CVPR. 770--778. Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016. Deep Residual Learning for Image Recognition. In CVPR. 770--778."},{"key":"e_1_3_2_1_18_1","volume-title":"Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift. In ICML. 448--456.","author":"Ioffe Sergey","year":"2015","unstructured":"Sergey Ioffe and Christian Szegedy . 2015 . Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift. In ICML. 448--456. Sergey Ioffe and Christian Szegedy. 2015. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift. In ICML. 448--456."},{"key":"e_1_3_2_1_19_1","volume-title":"Bandit algorithms","author":"Lattimore Tor","unstructured":"Tor Lattimore and Csaba Szepesv\u00e1ri . 2020. Bandit algorithms . Cambridge University Press . Tor Lattimore and Csaba Szepesv\u00e1ri. 2020. Bandit algorithms. Cambridge University Press."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"crossref","unstructured":"Pan Li Zhen Qin Xuanhui Wang and Donald Metzler. 2019. Combining Decision Trees and Neural Networks for Learning-to-Rank in Personal Search. In KDD. 2032--2040. Pan Li Zhen Qin Xuanhui Wang and Donald Metzler. 2019. Combining Decision Trees and Neural Networks for Learning-to-Rank in Personal Search. In KDD. 2032--2040.","DOI":"10.1145\/3292500.3330676"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"crossref","unstructured":"Jianxun Lian Xiaohuan Zhou Fuzheng Zhang Zhongxia Chen Xing Xie and Guangzhong Sun. 2018. xdeepfm: Combining explicit and implicit feature interactions for recommender systems. In KDD. 1754--1763. Jianxun Lian Xiaohuan Zhou Fuzheng Zhang Zhongxia Chen Xing Xie and Guangzhong Sun. 2018. xdeepfm: Combining explicit and implicit feature interactions for recommender systems. In KDD. 1754--1763.","DOI":"10.1145\/3219819.3220023"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"crossref","unstructured":"David C. Liu Stephanie Rogers Raymond Shiau Dmitry Kislyuk Kevin C. Ma Zhigang Zhong Jenny Liu and Yushi Jing. 2017. Related Pins at Pinterest: The Evolution of a Real-World Recommender System. In WWW. 583--592. David C. Liu Stephanie Rogers Raymond Shiau Dmitry Kislyuk Kevin C. Ma Zhigang Zhong Jenny Liu and Yushi Jing. 2017. Related Pins at Pinterest: The Evolution of a Real-World Recommender System. In WWW. 583--592.","DOI":"10.1145\/3041021.3054202"},{"key":"e_1_3_2_1_23_1","first-page":"3","article-title":"Learning to Rank for Information Retrieval","volume":"3","author":"Liu Tie-Yan","year":"2009","unstructured":"Tie-Yan Liu . 2009 . Learning to Rank for Information Retrieval . Found. Trends Inf. Retr. , Vol. 3 , 3 (March 2009), 225--331. Tie-Yan Liu. 2009. Learning to Rank for Information Retrieval. Found. Trends Inf. Retr., Vol. 3, 3 (March 2009), 225--331.","journal-title":"Found. Trends Inf. Retr."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"crossref","unstructured":"Rama Kumar Pasumarthi Xuanhui Wang Cheng Li Sebastian Bruch Michael Bendersky Marc Najork Jan Pfeifer Nadav Golbandi Rohan Anil and Stephan Wolf. 2019. TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank. In KDD. Rama Kumar Pasumarthi Xuanhui Wang Cheng Li Sebastian Bruch Michael Bendersky Marc Najork Jan Pfeifer Nadav Golbandi Rohan Anil and Stephan Wolf. 2019. TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank. In KDD.","DOI":"10.1145\/3292500.3330677"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"crossref","unstructured":"Zhen Qin Suming J. Chen Donald Metzler Yongwoo Noh Jingzheng Qin and Xuanhui Wang. 2020. Attribute-based Propensity for Unbiased Learning in Recommender Systems: Algorithm and Case Studies. In KDD. Zhen Qin Suming J. Chen Donald Metzler Yongwoo Noh Jingzheng Qin and Xuanhui Wang. 2020. Attribute-based Propensity for Unbiased Learning in Recommender Systems: Algorithm and Case Studies. In KDD.","DOI":"10.1145\/3394486.3403285"},{"key":"e_1_3_2_1_26_1","unstructured":"Tobias Schnabel Adith Swaminathan Ashudeep Singh Navin Chandak and Thorsten Joachims. 2016. Recommendations as Treatments: Debiasing Learning and Evaluation. In ICML. 1670--1679. Tobias Schnabel Adith Swaminathan Ashudeep Singh Navin Chandak and Thorsten Joachims. 2016. Recommendations as Treatments: Debiasing Learning and Evaluation. In ICML. 1670--1679."},{"key":"e_1_3_2_1_27_1","unstructured":"Sandeep Tata Vlad Panait Suming J. Chen and Mike Colagrosso. 2019. ItemSuggest: A Data Management Platform for Machine Learned Ranking Services. In CIDR. Sandeep Tata Vlad Panait Suming J. Chen and Mike Colagrosso. 2019. ItemSuggest: A Data Management Platform for Machine Learned Ranking Services. In CIDR."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098048"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"crossref","unstructured":"Ruoxi Wang Bin Fu Gang Fu and Mingliang Wang. 2017. Deep & cross network for ad click predictions. In ADKDD. 1--7. Ruoxi Wang Bin Fu Gang Fu and Mingliang Wang. 2017. Deep & cross network for ad click predictions. In ADKDD. 1--7.","DOI":"10.1145\/3124749.3124754"},{"key":"e_1_3_2_1_30_1","volume-title":"Mianwei Zhou, Hua Ouyang, Jianhui Chen, Changsung Kang, Hongbo Deng, Chikashi Nobata, Jean-Marc Langlois, and Yi Chang.","author":"Yin Dawei","year":"2016","unstructured":"Dawei Yin , Yuening Hu , Jiliang Tang , Tim Daly Jr ., Mianwei Zhou, Hua Ouyang, Jianhui Chen, Changsung Kang, Hongbo Deng, Chikashi Nobata, Jean-Marc Langlois, and Yi Chang. 2016 . Ranking Relevance in Yahoo Search. In KDD. 323--332. Dawei Yin, Yuening Hu, Jiliang Tang, Tim Daly Jr., Mianwei Zhou, Hua Ouyang, Jianhui Chen, Changsung Kang, Hongbo Deng, Chikashi Nobata, Jean-Marc Langlois, and Yi Chang. 2016. Ranking Relevance in Yahoo Search. In KDD. 323--332."},{"key":"e_1_3_2_1_31_1","first-page":"1","article-title":"Deep Learning Based Recommender System","volume":"52","author":"Zhang Shuai","year":"2019","unstructured":"Shuai Zhang , Lina Yao , Aixin Sun , and Yi Tay . 2019 . Deep Learning Based Recommender System : A Survey and New Perspectives. ACM Comput. Surv. , Vol. 52 , 1 (Feb. 2019), 5:1--5:38. Shuai Zhang, Lina Yao, Aixin Sun, and Yi Tay. 2019. Deep Learning Based Recommender System: A Survey and New Perspectives. ACM Comput. Surv., Vol. 52, 1 (Feb. 2019), 5:1--5:38.","journal-title":"A Survey and New Perspectives. ACM Comput. Surv."},{"key":"e_1_3_2_1_32_1","volume-title":"Chi","author":"Zhao Zhe","year":"2019","unstructured":"Zhe Zhao , Lichan Hong , Li Wei , Jilin Chen , Aniruddh Nath , Shawn Andrews , Aditee Kumthekar , Maheswaran Sathiamoorthy , Xinyang Yi , and Ed Chi . 2019 . Recommending what video to watch next: a multitask ranking system. In RecSys. ACM , 43--51. Zhe Zhao, Lichan Hong, Li Wei, Jilin Chen, Aniruddh Nath, Shawn Andrews, Aditee Kumthekar, Maheswaran Sathiamoorthy, Xinyang Yi, and Ed Chi. 2019. Recommending what video to watch next: a multitask ranking system. In RecSys. ACM, 43--51."}],"event":{"name":"KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Virtual Event CA USA","acronym":"KDD '20","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394486.3403341","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3394486.3403341","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T21:31:29Z","timestamp":1750195889000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394486.3403341"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8,20]]},"references-count":32,"alternative-id":["10.1145\/3394486.3403341","10.1145\/3394486"],"URL":"https:\/\/doi.org\/10.1145\/3394486.3403341","relation":{},"subject":[],"published":{"date-parts":[[2020,8,20]]},"assertion":[{"value":"2020-08-20","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}