{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:19:44Z","timestamp":1750220384621,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":55,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,8,14]],"date-time":"2021-08-14T00:00:00Z","timestamp":1628899200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,8,14]]},"DOI":"10.1145\/3447548.3467192","type":"proceedings-article","created":{"date-parts":[[2021,8,12]],"date-time":"2021-08-12T06:12:05Z","timestamp":1628748725000},"page":"3817-3825","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Towards the D-Optimal Online Experiment Design for Recommender Selection"],"prefix":"10.1145","author":[{"given":"Da","family":"Xu","sequence":"first","affiliation":[{"name":"Walmart Labs, Sunnyvale, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chuanwei","family":"Ruan","sequence":"additional","affiliation":[{"name":"Walmart Labs, Sunnyvale, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Evren","family":"Korpeoglu","sequence":"additional","affiliation":[{"name":"Walmart Labs, Sunnyvale, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sushant","family":"Kumar","sequence":"additional","affiliation":[{"name":"Walmart Labs, Sunnyvale, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kannan","family":"Achan","sequence":"additional","affiliation":[{"name":"Walmart Labs, Sunnyvale, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,8,14]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"COLT Workshop on On-line Learning with Limited Feedback","volume":"92","author":"Abbasi-Yadkori Yasin","year":"2009","unstructured":"Yasin Abbasi-Yadkori , Andr\u00e1s Antos , and Csaba Szepesv\u00e1ri . 2009 . Forced-exploration based algorithms for playing in stochastic linear bandits . In COLT Workshop on On-line Learning with Limited Feedback , Vol. 92 . 236. Yasin Abbasi-Yadkori, Andr\u00e1s Antos, and Csaba Szepesv\u00e1ri. 2009. Forced-exploration based algorithms for playing in stochastic linear bandits. In COLT Workshop on On-line Learning with Limited Feedback, Vol. 92. 236."},{"key":"e_1_3_2_1_2_1","volume-title":"International Conference on Machine Learning. 1638--1646","author":"Agarwal Alekh","year":"2014","unstructured":"Alekh Agarwal , Daniel Hsu , Satyen Kale , John Langford , Lihong Li , and Robert Schapire . 2014 . Taming the monster: A fast and simple algorithm for contextual bandits . In International Conference on Machine Learning. 1638--1646 . Alekh Agarwal, Daniel Hsu, Satyen Kale, John Langford, Lihong Li, and Robert Schapire. 2014. Taming the monster: A fast and simple algorithm for contextual bandits. In International Conference on Machine Learning. 1638--1646."},{"key":"e_1_3_2_1_3_1","volume-title":"Conference on learning theory. 39--1.","author":"Agrawal Shipra","year":"2012","unstructured":"Shipra Agrawal and Navin Goyal . 2012 . Analysis of thompson sampling for the multi-armed bandit problem . In Conference on learning theory. 39--1. Shipra Agrawal and Navin Goyal. 2012. Analysis of thompson sampling for the multi-armed bandit problem. In Conference on learning theory. 39--1."},{"key":"e_1_3_2_1_4_1","series-title":"SIAM journal on computing","volume-title":"The nonstochastic multiarmed bandit problem","author":"Auer Peter","year":"2002","unstructured":"Peter Auer , Nicolo Cesa-Bianchi , Yoav Freund , and Robert E Schapire . 2002. The nonstochastic multiarmed bandit problem . SIAM journal on computing , Vol. 32 , 1 ( 2002 ), 48--77. Peter Auer, Nicolo Cesa-Bianchi, Yoav Freund, and Robert E Schapire. 2002. The nonstochastic multiarmed bandit problem. SIAM journal on computing, Vol. 32, 1 (2002), 48--77."},{"key":"e_1_3_2_1_5_1","volume-title":"Conference on Learning Theory. 116--120","author":"Auer Peter","year":"2016","unstructured":"Peter Auer and Chao-Kai Chiang . 2016 . An algorithm with nearly optimal pseudo-regret for both stochastic and adversarial bandits . In Conference on Learning Theory. 116--120 . Peter Auer and Chao-Kai Chiang. 2016. An algorithm with nearly optimal pseudo-regret for both stochastic and adversarial bandits. In Conference on Learning Theory. 116--120."},{"key":"e_1_3_2_1_6_1","volume-title":"Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics. 19--26","author":"Beygelzimer Alina","year":"2011","unstructured":"Alina Beygelzimer , John Langford , Lihong Li , Lev Reyzin , and Robert Schapire . 2011 . Contextual bandit algorithms with supervised learning guarantees . In Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics. 19--26 . Alina Beygelzimer, John Langford, Lihong Li, Lev Reyzin, and Robert Schapire. 2011. Contextual bandit algorithms with supervised learning guarantees. In Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics. 19--26."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3172944.3172967"},{"key":"e_1_3_2_1_8_1","volume-title":"Conference on Learning Theory. JMLR Workshop and Conference Proceedings, 41--1.","author":"Bubeck S\u00e9bastien","year":"2012","unstructured":"S\u00e9bastien Bubeck , Nicolo Cesa-Bianchi , and Sham M Kakade . 2012 . Towards minimax policies for online linear optimization with bandit feedback . In Conference on Learning Theory. JMLR Workshop and Conference Proceedings, 41--1. S\u00e9bastien Bubeck, Nicolo Cesa-Bianchi, and Sham M Kakade. 2012. Towards minimax policies for online linear optimization with bandit feedback. In Conference on Learning Theory. JMLR Workshop and Conference Proceedings, 41--1."},{"key":"e_1_3_2_1_9_1","volume-title":"Conference on Learning Theory. 42--1.","author":"Bubeck S\u00e9bastien","year":"2012","unstructured":"S\u00e9bastien Bubeck and Aleksandrs Slivkins . 2012 . The best of both worlds: Stochastic and adversarial bandits . In Conference on Learning Theory. 42--1. S\u00e9bastien Bubeck and Aleksandrs Slivkins. 2012. The best of both worlds: Stochastic and adversarial bandits. In Conference on Learning Theory. 42--1."},{"key":"e_1_3_2_1_10_1","volume-title":"Proceedings of the 13th ACM Conference on Recommender Systems. 432--436","author":"Rocio Ca","year":"2019","unstructured":"Rocio Ca namares, Marcos Redondo , and Pablo Castells . 2019 . Multi-armed recommender system bandit ensembles . In Proceedings of the 13th ACM Conference on Recommender Systems. 432--436 . Rocio Ca namares, Marcos Redondo, and Pablo Castells. 2019. Multi-armed recommender system bandit ensembles. In Proceedings of the 13th ACM Conference on Recommender Systems. 432--436."},{"key":"e_1_3_2_1_11_1","unstructured":"Olivier Chapelle and Lihong Li. 2011. An empirical evaluation of thompson sampling. In Advances in neural information processing systems. 2249--2257.  Olivier Chapelle and Lihong Li. 2011. An empirical evaluation of thompson sampling. In Advances in neural information processing systems. 2249--2257."},{"key":"e_1_3_2_1_12_1","volume-title":"Bias and Debias in Recommender System: A Survey and Future Directions. arXiv preprint arXiv:2010.03240","author":"Chen Jiawei","year":"2020","unstructured":"Jiawei Chen , Hande Dong , Xiang Wang , Fuli Feng , Meng Wang , and Xiangnan He. 2020. Bias and Debias in Recommender System: A Survey and Future Directions. arXiv preprint arXiv:2010.03240 ( 2020 ). Jiawei Chen, Hande Dong, Xiang Wang, Fuli Feng, Meng Wang, and Xiangnan He. 2020. Bias and Debias in Recommender System: A Survey and Future Directions. arXiv preprint arXiv:2010.03240 (2020)."},{"key":"e_1_3_2_1_13_1","volume-title":"Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics. 208--214","author":"Chu Wei","year":"2011","unstructured":"Wei Chu , Lihong Li , Lev Reyzin , and Robert Schapire . 2011 . Contextual bandits with linear payoff functions . In Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics. 208--214 . Wei Chu, Lihong Li, Lev Reyzin, and Robert Schapire. 2011. Contextual bandits with linear payoff functions. In Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics. 208--214."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/57.3.551"},{"volume-title":"International Conference on Learning Representations (ICLR).","key":"e_1_3_2_1_15_1","unstructured":"da Xu, chuanwei ruan, evren korpeoglu, sushant kumar , and kannan achan. 2020. Inductive representation learning on temporal graphs . In International Conference on Learning Representations (ICLR). da Xu, chuanwei ruan, evren korpeoglu, sushant kumar, and kannan achan. 2020. Inductive representation learning on temporal graphs. In International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_16_1","volume-title":"Efficient optimal learning for contextual bandits. arXiv preprint arXiv:1106.2369","author":"Dudik Miroslav","year":"2011","unstructured":"Miroslav Dudik , Daniel Hsu , Satyen Kale , Nikos Karampatziakis , John Langford , Lev Reyzin , and Tong Zhang . 2011. Efficient optimal learning for contextual bandits. arXiv preprint arXiv:1106.2369 ( 2011 ). Miroslav Dudik, Daniel Hsu, Satyen Kale, Nikos Karampatziakis, John Langford, Lev Reyzin, and Tong Zhang. 2011. Efficient optimal learning for contextual bandits. arXiv preprint arXiv:1106.2369 (2011)."},{"key":"e_1_3_2_1_17_1","first-page":"682","article-title":"The augmentation of experimental data to maximize [X? X]","volume":"13","author":"Dykstra Otto","year":"1971","unstructured":"Otto Dykstra . 1971 . The augmentation of experimental data to maximize [X? X] . Technometrics , Vol. 13 , 3 (1971), 682 -- 688 . Otto Dykstra. 1971. The augmentation of experimental data to maximize [X? X]. Technometrics, Vol. 13, 3 (1971), 682--688.","journal-title":"Technometrics"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"crossref","unstructured":"Marguerite Frank Philip Wolfe etal 1956. An algorithm for quadratic programming. Naval research logistics quarterly Vol. 3 1--2 (1956) 95--110.  Marguerite Frank Philip Wolfe et al. 1956. An algorithm for quadratic programming. Naval research logistics quarterly Vol. 3 1--2 (1956) 95--110.","DOI":"10.1002\/nav.3800030109"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3159652.3159687"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.5555\/2946645.3007072"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/963770.963772"},{"volume-title":"Collaborative Filtering for Implicit Feedback Datasets. In 2008 Eighth IEEE International Conference on Data Mining. 263--272","author":"Hu Y.","key":"e_1_3_2_1_22_1","unstructured":"Y. Hu , Y. Koren , and C. Volinsky . 2008 . Collaborative Filtering for Implicit Feedback Datasets. In 2008 Eighth IEEE International Conference on Data Mining. 263--272 . Y. Hu, Y. Koren, and C. Volinsky. 2008. Collaborative Filtering for Implicit Feedback Datasets. In 2008 Eighth IEEE International Conference on Data Mining. 263--272."},{"volume-title":"Causal inference in statistics, social, and biomedical sciences","author":"Imbens Guido W","key":"e_1_3_2_1_23_1","unstructured":"Guido W Imbens and Donald B Rubin . 2015. Causal inference in statistics, social, and biomedical sciences . Cambridge University Press . Guido W Imbens and Donald B Rubin. 2015. Causal inference in statistics, social, and biomedical sciences .Cambridge University Press."},{"key":"e_1_3_2_1_24_1","volume-title":"Proceedings of the 30th international conference on machine learning. 427--435","author":"Jaggi Martin","year":"2013","unstructured":"Martin Jaggi . 2013 . Revisiting Frank-Wolfe: Projection-free sparse convex optimization . In Proceedings of the 30th international conference on machine learning. 427--435 . Martin Jaggi. 2013. Revisiting Frank-Wolfe: Projection-free sparse convex optimization. In Proceedings of the 30th international conference on machine learning. 427--435."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/1835804.1835893"},{"key":"e_1_3_2_1_26_1","first-page":"271","article-title":"Some guidelines for constructing exact D-optimal designs on convex design spaces","volume":"25","author":"Johnson Mark E","year":"1983","unstructured":"Mark E Johnson and Christopher J Nachtsheim . 1983 . Some guidelines for constructing exact D-optimal designs on convex design spaces . Technometrics , Vol. 25 , 3 (1983), 271 -- 277 . Mark E Johnson and Christopher J Nachtsheim. 1983. Some guidelines for constructing exact D-optimal designs on convex design spaces. Technometrics, Vol. 25, 3 (1983), 271--277.","journal-title":"Technometrics"},{"key":"e_1_3_2_1_27_1","unstructured":"Jaya Kawale Hung H Bui Branislav Kveton Long Tran-Thanh and Sanjay Chawla. 2015. Efficient Thompson Sampling for Online? Matrix-Factorization Recommendation. In Advances in neural information processing systems. 1297--1305.  Jaya Kawale Hung H Bui Branislav Kveton Long Tran-Thanh and Sanjay Chawla. 2015. Efficient Thompson Sampling for Online? Matrix-Factorization Recommendation. In Advances in neural information processing systems. 1297--1305."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.4153\/CJM-1960-030-4"},{"key":"e_1_3_2_1_29_1","unstructured":"John Langford and Tong Zhang. 2008. The epoch-greedy algorithm for multi-armed bandits with side information. In Advances in neural information processing systems. 817--824.  John Langford and Tong Zhang. 2008. The epoch-greedy algorithm for multi-armed bandits with side information. In Advances in neural information processing systems. 817--824."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219905"},{"key":"e_1_3_2_1_31_1","volume-title":"Proceedings of the Workshop on On-line Trading of Exploration and Exploitation 2. 19--36","author":"Li Lihong","year":"2012","unstructured":"Lihong Li , Wei Chu , John Langford , Taesup Moon , and Xuanhui Wang . 2012 . An unbiased offline evaluation of contextual bandit algorithms with generalized linear models . In Proceedings of the Workshop on On-line Trading of Exploration and Exploitation 2. 19--36 . Lihong Li, Wei Chu, John Langford, Taesup Moon, and Xuanhui Wang. 2012. An unbiased offline evaluation of contextual bandit algorithms with generalized linear models. In Proceedings of the Workshop on On-line Trading of Exploration and Exploitation 2. 19--36."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/1772690.1772758"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/2911451.2911548"},{"key":"e_1_3_2_1_34_1","volume-title":"Conference On Learning Theory. 1739--1776","author":"Luo Haipeng","year":"2018","unstructured":"Haipeng Luo , Chen-Yu Wei , Alekh Agarwal , and John Langford . 2018 . Efficient contextual bandits in non-stationary worlds . In Conference On Learning Theory. 1739--1776 . Haipeng Luo, Chen-Yu Wei, Alekh Agarwal, and John Langford. 2018. Efficient contextual bandits in non-stationary worlds. In Conference On Learning Theory. 1739--1776."},{"key":"e_1_3_2_1_35_1","first-page":"465","article-title":"A method for constructing an optimal regression design after an initial set of input values has been selected","volume":"2","author":"Mayer Lawrenca S","year":"1973","unstructured":"Lawrenca S Mayer and Arlo D Hendrickson . 1973 . A method for constructing an optimal regression design after an initial set of input values has been selected . Communications in Statistics-Theory and Methods , Vol. 2 , 5 (1973), 465 -- 477 . Lawrenca S Mayer and Arlo D Hendrickson. 1973. A method for constructing an optimal regression design after an initial set of input values has been selected. Communications in Statistics-Theory and Methods, Vol. 2, 5 (1973), 465--477.","journal-title":"Communications in Statistics-Theory and Methods"},{"key":"e_1_3_2_1_36_1","unstructured":"H Brendan McMahan and Matthew Streeter. 2009. Tighter bounds for multi-armed bandits with expert advice. (2009).  H Brendan McMahan and Matthew Streeter. 2009. Tighter bounds for multi-armed bandits with expert advice. (2009)."},{"key":"e_1_3_2_1_37_1","unstructured":"Tomas Mikolov Ilya Sutskever Kai Chen Greg Corrado and Jeffrey Dean. 2013. Distributed Representations of Words and Phrases and their Compositionality. arxiv: 1310.4546 [cs.CL]  Tomas Mikolov Ilya Sutskever Kai Chen Greg Corrado and Jeffrey Dean. 2013. Distributed Representations of Words and Phrases and their Compositionality. arxiv: 1310.4546 [cs.CL]"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1198\/0003130032378"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1090\/S0002-9904-1952-09620-8"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1287\/moor.1100.0446"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.5555\/2946645.3007021"},{"key":"e_1_3_2_1_42_1","volume-title":"Abbas Kazerouni, Ian Osband, and Zheng Wen.","author":"Russo Daniel","year":"2017","unstructured":"Daniel Russo , Benjamin Van Roy , Abbas Kazerouni, Ian Osband, and Zheng Wen. 2017 . A tutorial on thompson sampling. arXiv preprint arXiv:1707.02038 (2017). Daniel Russo, Benjamin Van Roy, Abbas Kazerouni, Ian Osband, and Zheng Wen. 2017. A tutorial on thompson sampling. arXiv preprint arXiv:1707.02038 (2017)."},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/371920.372071"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/2766462.2767695"},{"volume-title":"Recommender systems handbook","author":"Shani Guy","key":"e_1_3_2_1_45_1","unstructured":"Guy Shani and Asela Gunawardana . 2011. Evaluating recommendation systems . In Recommender systems handbook . Springer , 257--297. Guy Shani and Asela Gunawardana. 2011. Evaluating recommendation systems. In Recommender systems handbook. Springer, 257--297."},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/25.3-4.285"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/60.2.345"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219860"},{"key":"e_1_3_2_1_49_1","first-page":"799","article-title":"a. Methods and apparatus for item substitution","volume":"16","author":"Xu Da","year":"2020","unstructured":"Da Xu , RUAN Chuanwei , Kamiya Motwani , Evren Korpeoglu , Sushant Kumar , and Kannan Achan . 2020 a. Methods and apparatus for item substitution . US Patent App. 16\/424 , 799 . Da Xu, RUAN Chuanwei, Kamiya Motwani, Evren Korpeoglu, Sushant Kumar, and Kannan Achan. 2020 a. Methods and apparatus for item substitution. US Patent App. 16\/424,799.","journal-title":"US Patent App."},{"key":"e_1_3_2_1_50_1","volume-title":"Adversarial Counterfactual Learning and Evaluation for Recommender System. Advances in Neural Information Processing Systems","volume":"33","author":"Xu Da","year":"2020","unstructured":"Da Xu , Chuanwei Ruan , Evren Korpeoglu , Sushant Kumar , and Kannan Achan . 2020 b . Adversarial Counterfactual Learning and Evaluation for Recommender System. Advances in Neural Information Processing Systems , Vol. 33 (2020). Da Xu, Chuanwei Ruan, Evren Korpeoglu, Sushant Kumar, and Kannan Achan. 2020 b. Adversarial Counterfactual Learning and Evaluation for Recommender System. Advances in Neural Information Processing Systems, Vol. 33 (2020)."},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371778"},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2013.806268"},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330769"},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1145\/2505515.2505690"},{"volume-title":"User-Based Collaborative-Filtering Recommendation Algorithms on Hadoop. In 2010 Third International Conference on Knowledge Discovery and Data Mining. 478--481","author":"Zhao Z.","key":"e_1_3_2_1_55_1","unstructured":"Z. Zhao and M. Shang . 2010 . User-Based Collaborative-Filtering Recommendation Algorithms on Hadoop. In 2010 Third International Conference on Knowledge Discovery and Data Mining. 478--481 . Z. Zhao and M. Shang. 2010. User-Based Collaborative-Filtering Recommendation Algorithms on Hadoop. In 2010 Third International Conference on Knowledge Discovery and Data Mining. 478--481."}],"event":{"name":"KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"],"location":"Virtual Event Singapore","acronym":"KDD '21"},"container-title":["Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery &amp; Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3447548.3467192","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3447548.3467192","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:18:27Z","timestamp":1750191507000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3447548.3467192"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,14]]},"references-count":55,"alternative-id":["10.1145\/3447548.3467192","10.1145\/3447548"],"URL":"https:\/\/doi.org\/10.1145\/3447548.3467192","relation":{},"subject":[],"published":{"date-parts":[[2021,8,14]]},"assertion":[{"value":"2021-08-14","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}