{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:09:14Z","timestamp":1750219754020,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":76,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,10,21]],"date-time":"2023-10-21T00:00:00Z","timestamp":1697846400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["IIS #2007932"],"award-info":[{"award-number":["IIS #2007932"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,10,21]]},"DOI":"10.1145\/3583780.3614874","type":"proceedings-article","created":{"date-parts":[[2023,10,21]],"date-time":"2023-10-21T07:45:42Z","timestamp":1697874342000},"page":"152-162","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Fair&Share: Fast and Fair Multi-Criteria Selections"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1260-0914","authenticated-orcid":false,"given":"Kathleen","family":"Cachel","sequence":"first","affiliation":[{"name":"Worcester Polytechnic Institute, Worcester, MA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5375-9254","authenticated-orcid":false,"given":"Elke","family":"Rundensteiner","sequence":"additional","affiliation":[{"name":"Worcester Polytechnic Institute, Worcester, MA, USA"}]}],"member":"320","published-online":{"date-parts":[[2023,10,21]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"international conference on Very large data bases (VLDB). ACM, 495--506","author":"Akbarinia Reza","year":"2007","unstructured":"Reza Akbarinia , Esther Pacitti , and Patrick Valduriez . 2007 . Best position algorithms for top-k queries . In international conference on Very large data bases (VLDB). ACM, 495--506 . Reza Akbarinia, Esther Pacitti, and Patrick Valduriez. 2007. Best position algorithms for top-k queries. In international conference on Very large data bases (VLDB). ACM, 495--506."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3299869.3300079"},{"key":"e_1_3_2_1_3_1","volume-title":"International Conference on Machine Learning. PMLR, 405--413","author":"Backurs Arturs","year":"2019","unstructured":"Arturs Backurs , Piotr Indyk , Krzysztof Onak , Baruch Schieber , Ali Vakilian , and Tal Wagner . 2019 . Scalable fair clustering . In International Conference on Machine Learning. PMLR, 405--413 . Arturs Backurs, Piotr Indyk, Krzysztof Onak, Baruch Schieber, Ali Vakilian, and Tal Wagner. 2019. Scalable fair clustering. In International Conference on Machine Learning. PMLR, 405--413."},{"key":"e_1_3_2_1_4_1","volume-title":"Fair algorithms for clustering. arXiv preprint arXiv:1901.02393","author":"Bera Suman K","year":"2019","unstructured":"Suman K Bera , Deeparnab Chakrabarty , Nicolas J Flores , and Maryam Negahbani . 2019. Fair algorithms for clustering. arXiv preprint arXiv:1901.02393 ( 2019 ). Suman K Bera, Deeparnab Chakrabarty, Nicolas J Flores, and Maryam Negahbani. 2019. Fair algorithms for clustering. arXiv preprint arXiv:1901.02393 (2019)."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939718"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11457"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3514094.3534160"},{"key":"e_1_3_2_1_8_1","volume-title":"How to be fair and diverse? arXiv preprint arXiv:1610.07183","author":"Celis L Elisa","year":"2016","unstructured":"L Elisa Celis , Amit Deshpande , Tarun Kathuria , and Nisheeth K Vishnoi . 2016. How to be fair and diverse? arXiv preprint arXiv:1610.07183 ( 2016 ). L Elisa Celis, Amit Deshpande, Tarun Kathuria, and Nisheeth K Vishnoi. 2016. How to be fair and diverse? arXiv preprint arXiv:1610.07183 (2016)."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442188.3445930"},{"key":"e_1_3_2_1_10_1","volume-title":"Multiwinner voting with fairness constraints. arXiv preprint arXiv:1710.10057","author":"Celis L Elisa","year":"2017","unstructured":"L Elisa Celis , Lingxiao Huang , and Nisheeth K Vishnoi . 2017. Multiwinner voting with fairness constraints. arXiv preprint arXiv:1710.10057 ( 2017 ). L Elisa Celis, Lingxiao Huang, and Nisheeth K Vishnoi. 2017. Multiwinner voting with fairness constraints. arXiv preprint arXiv:1710.10057 (2017)."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3351095.3372858"},{"key":"e_1_3_2_1_12_1","volume-title":"Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining","author":"Chen Minmin","year":"2018","unstructured":"Minmin Chen , Alex Beutel , Paul Covington , Sagar Jain , Francois Belletti , and Ed H. Chi . 2018. Top-K Off-Policy Correction for a REINFORCE Recommender System . Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining ( 2018 ). Minmin Chen, Alex Beutel, Paul Covington, Sagar Jain, Francois Belletti, and Ed H. Chi. 2018. Top-K Off-Policy Correction for a REINFORCE Recommender System. Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining (2018)."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3114099"},{"key":"e_1_3_2_1_14_1","volume-title":"Fair clustering through fairlets. arXiv preprint arXiv:1802.05733","author":"Chierichetti Flavio","year":"2018","unstructured":"Flavio Chierichetti , Ravi Kumar , Silvio Lattanzi , and Sergei Vassilvitskii . 2018. Fair clustering through fairlets. arXiv preprint arXiv:1802.05733 ( 2018 ). Flavio Chierichetti, Ravi Kumar, Silvio Lattanzi, and Sergei Vassilvitskii. 2018. Fair clustering through fairlets. arXiv preprint arXiv:1802.05733 (2018)."},{"key":"e_1_3_2_1_15_1","volume-title":"International Conference on Machine Learning. PMLR","author":"Chiplunkar Ashish","year":"2020","unstructured":"Ashish Chiplunkar , Sagar Kale , and Sivaramakrishnan Natarajan Ramamoorthy . 2020 . How to solve fair k-center in massive data models . In International Conference on Machine Learning. PMLR , 1877--1886. Ashish Chiplunkar, Sagar Kale, and Sivaramakrishnan Natarajan Ramamoorthy. 2020. How to solve fair k-center in massive data models. In International Conference on Machine Learning. PMLR, 1877--1886."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3318464.3389729"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271753"},{"key":"e_1_3_2_1_18_1","first-page":"870","article-title":"Tackling unconscious bias in hiring practices: The plight of the Rooney rule","volume":"82","author":"Collins Brian W","year":"2007","unstructured":"Brian W Collins . 2007 . Tackling unconscious bias in hiring practices: The plight of the Rooney rule . NYUL Rev. , Vol. 82 (2007), 870 . Brian W Collins. 2007. Tackling unconscious bias in hiring practices: The plight of the Rooney rule. NYUL Rev. , Vol. 82 (2007), 870.","journal-title":"NYUL Rev."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/2959100.2959190"},{"key":"e_1_3_2_1_20_1","volume-title":"State of the Art, and Challenges. ArXiv","author":"Deldjoo Yashar","year":"1803","unstructured":"Yashar Deldjoo , Markus Schedl , and Peter Knees . 2021. Content-driven Music Recommendation: Evolution , State of the Art, and Challenges. ArXiv , Vol. abs\/ 2107 .1 1803 (2021). Yashar Deldjoo, Markus Schedl, and Peter Knees. 2021. Content-driven Music Recommendation: Evolution, State of the Art, and Challenges. ArXiv , Vol. abs\/2107.11803 (2021)."},{"key":"e_1_3_2_1_21_1","volume-title":"Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkits. 2022 ACM Conference on Fairness, Accountability, and Transparency","author":"Deng Wesley Hanwen","year":"2022","unstructured":"Wesley Hanwen Deng , Manish Nagireddy , Michelle Seng Ah Lee , Jatinder Singh , Zhiwei Steven Wu , Kenneth Holstein , and Haiyi Zhu . 2022 . Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkits. 2022 ACM Conference on Fairness, Accountability, and Transparency (2022). Wesley Hanwen Deng, Manish Nagireddy, Michelle Seng Ah Lee, Jatinder Singh, Zhiwei Steven Wu, Kenneth Holstein, and Haiyi Zhu. 2022. Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkits. 2022 ACM Conference on Fairness, Accountability, and Transparency (2022)."},{"key":"e_1_3_2_1_22_1","volume-title":"Success and shortfalls in effort to diversify nfl coaching. The New York Times","author":"Jeremi Duru N","year":"2015","unstructured":"N Jeremi Duru and David Waldstein . 2015. Success and shortfalls in effort to diversify nfl coaching. The New York Times ( 2015 ). N Jeremi Duru and David Waldstein. 2015. Success and shortfalls in effort to diversify nfl coaching. The New York Times (2015)."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/2090236.2090255"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3391403.3399482"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1006\/jcss.1998.1600"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/565117.565143"},{"key":"e_1_3_2_1_27_1","unstructured":"Nicholas Fandos. 2020. Senators lead an increasingly diverse nation. their top aides are mostly white. https:\/\/www.nytimes.com\/2020\/08\/21\/us\/politics\/top-senate-aides-diversity.html  Nicholas Fandos. 2020. Senators lead an increasingly diverse nation. their top aides are mostly white. https:\/\/www.nytimes.com\/2020\/08\/21\/us\/politics\/top-senate-aides-diversity.html"},{"key":"e_1_3_2_1_28_1","volume-title":"Equality of opportunity in supervised learning. Advances in neural information processing systems","author":"Hardt Moritz","year":"2016","unstructured":"Moritz Hardt , Eric Price , and Nati Srebro . 2016. Equality of opportunity in supervised learning. Advances in neural information processing systems , Vol. 29 ( 2016 ), 3315--3323. Moritz Hardt, Eric Price, and Nati Srebro. 2016. Equality of opportunity in supervised learning. Advances in neural information processing systems , Vol. 29 (2016), 3315--3323."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/2648584.2648589"},{"key":"e_1_3_2_1_30_1","volume-title":"Elizabeth Mahon","author":"Huang Grant D.","year":"2018","unstructured":"Grant D. Huang , Jonca Bull , Kelly Johnston McKee , Elizabeth Mahon , Beth D Harper , and Jamie N. Roberts. 2018 . Clinical trials recruitment planning: A proposed framework from the Clinical Trials Transformation Initiative. Contemporary clinical trials , Vol. 66 (2018), 74--79. Grant D. Huang, Jonca Bull, Kelly Johnston McKee, Elizabeth Mahon, Beth D Harper, and Jamie N. Roberts. 2018. Clinical trials recruitment planning: A proposed framework from the Clinical Trials Transformation Initiative. Contemporary clinical trials , Vol. 66 (2018), 74--79."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3375627.3375848"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/775047.775067"},{"key":"e_1_3_2_1_33_1","volume-title":"International Conference on Machine Learning.","author":"Jones Matthew D.","year":"2020","unstructured":"Matthew D. Jones , Huy L. Nguyen , and Thy Nguyen . 2020 . Fair k-Centers via Maximum Matching . In International Conference on Machine Learning. Matthew D. Jones, Huy L. Nguyen, and Thy Nguyen. 2020. Fair k-Centers via Maximum Matching. In International Conference on Machine Learning."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICC.2012.6364049"},{"key":"e_1_3_2_1_35_1","volume-title":"International Conference on Machine Learning. PMLR","author":"Kearns Michael","year":"2017","unstructured":"Michael Kearns , Aaron Roth , and Zhiwei Steven Wu . 2017 . Meritocratic fairness for cross-population selection . In International Conference on Machine Learning. PMLR , 1828--1836. Michael Kearns, Aaron Roth, and Zhiwei Steven Wu. 2017. Meritocratic fairness for cross-population selection. In International Conference on Machine Learning. PMLR, 1828--1836."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1158\/1078-0432.CCR-20-3852"},{"key":"e_1_3_2_1_37_1","volume-title":"Selection problems in the presence of implicit bias. arXiv preprint arXiv:1801.03533","author":"Kleinberg Jon","year":"2018","unstructured":"Jon Kleinberg and Manish Raghavan . 2018. Selection problems in the presence of implicit bias. arXiv preprint arXiv:1801.03533 ( 2018 ). Jon Kleinberg and Manish Raghavan. 2018. Selection problems in the presence of implicit bias. arXiv preprint arXiv:1801.03533 (2018)."},{"key":"e_1_3_2_1_38_1","volume-title":"International Conference on Machine Learning. PMLR, 3458--3467","author":"Samadi Samira","year":"2019","unstructured":"Matth\"aus Kleindessner, Samira Samadi , Pranjal Awasthi , and Jamie Morgenstern . 2019 . Guarantees for spectral clustering with fairness constraints . In International Conference on Machine Learning. PMLR, 3458--3467 . Matth\"aus Kleindessner, Samira Samadi, Pranjal Awasthi, and Jamie Morgenstern. 2019. Guarantees for spectral clustering with fairness constraints. In International Conference on Machine Learning. PMLR, 3458--3467."},{"key":"e_1_3_2_1_39_1","volume-title":"Uci machine learning repository: adult data set. Avaliable: https:\/\/archive. ics. uci. edu\/ml\/machine-learning-databases\/adult","author":"Kohavi Ronny","year":"1996","unstructured":"Ronny Kohavi and Barry Becker . 1996. Uci machine learning repository: adult data set. Avaliable: https:\/\/archive. ics. uci. edu\/ml\/machine-learning-databases\/adult ( 1996 ). Ronny Kohavi and Barry Becker. 1996. Uci machine learning repository: adult data set. Avaliable: https:\/\/archive. ics. uci. edu\/ml\/machine-learning-databases\/adult (1996)."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2020.105507"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1080\/15332845.2011.588571"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/1272743.1272749"},{"key":"e_1_3_2_1_43_1","volume-title":"Advances in Neural Information Processing Systems","volume":"31","author":"Mandal Ankush","year":"2018","unstructured":"Ankush Mandal , He Jiang , Anshumali Shrivastava , and Vivek Sarkar . 2018 . Topkapi: parallel and fast sketches for finding top-K frequent elements . Advances in Neural Information Processing Systems , Vol. 31 (2018). Ankush Mandal, He Jiang, Anshumali Shrivastava, and Vivek Sarkar. 2018. Topkapi: parallel and fast sketches for finding top-K frequent elements. Advances in Neural Information Processing Systems , Vol. 31 (2018)."},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442188.3445887"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/3375627.3375832"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1613\/jair.1.13734"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.dss.2014.03.001"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00778-009-0174-x"},{"key":"e_1_3_2_1_49_1","volume-title":"Wall Street Journal","volume":"27","author":"Passariello Christina","year":"2016","unstructured":"Christina Passariello . 2016 . Tech firms borrow football play to increase hiring of women . Wall Street Journal , Vol. 27 (2016). Christina Passariello. 2016. Tech firms borrow football play to increase hiring of women. Wall Street Journal , Vol. 27 (2016)."},{"key":"e_1_3_2_1_50_1","volume-title":"The Impact of Representation Criteria on Human Bias in Hiring. In AAAI Conference on Human Computation & Crowdsourcing.","author":"Peng Andi","year":"2019","unstructured":"Andi Peng , Besmira Nushi , Emre K?cman, Kori Inkpen Quinn , Siddharth Suri , and Ece Kamar . 2019 . What You See Is What You Get? The Impact of Representation Criteria on Human Bias in Hiring. In AAAI Conference on Human Computation & Crowdsourcing. Andi Peng, Besmira Nushi, Emre K?cman, Kori Inkpen Quinn, Siddharth Suri, and Ece Kamar. 2019. What You See Is What You Get? The Impact of Representation Criteria on Human Bias in Hiring. In AAAI Conference on Human Computation & Crowdsourcing."},{"key":"e_1_3_2_1_51_1","volume-title":"On fairness and calibration. Advances in neural information processing systems","author":"Pleiss Geoff","year":"2017","unstructured":"Geoff Pleiss , Manish Raghavan , Felix Wu , Jon Kleinberg , and Kilian Q Weinberger . 2017. On fairness and calibration. Advances in neural information processing systems , Vol. 30 ( 2017 ). Geoff Pleiss, Manish Raghavan, Felix Wu, Jon Kleinberg, and Kilian Q Weinberger. 2017. On fairness and calibration. Advances in neural information processing systems , Vol. 30 (2017)."},{"key":"e_1_3_2_1_52_1","volume-title":"Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency","author":"Raghavan M.","year":"2019","unstructured":"M. Raghavan , Solon Barocas , Jon M. Kleinberg , and Karen E. C. Levy . 2019. Mitigating bias in algorithmic hiring: evaluating claims and practices . Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency ( 2019 ). M. Raghavan, Solon Barocas, Jon M. Kleinberg, and Karen E. C. Levy. 2019. Mitigating bias in algorithmic hiring: evaluating claims and practices. Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (2019)."},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2007.367934"},{"key":"e_1_3_2_1_54_1","unstructured":"Stephen E. Robertson. 1997. The probability ranking principle in IR.  Stephen E. Robertson. 1997. The probability ranking principle in IR."},{"key":"e_1_3_2_1_55_1","volume-title":"RecoGym: A Reinforcement Learning Environment for the problem of Product Recommendation in Online Advertising. ArXiv","author":"Rohde David","year":"2018","unstructured":"David Rohde , Stephen Bonner , Travis Dunlop , Flavian Vasile , and Alexandros Karatzoglou . 2018. RecoGym: A Reinforcement Learning Environment for the problem of Product Recommendation in Online Advertising. ArXiv , Vol. abs\/ 1808 .00720 ( 2018 ). David Rohde, Stephen Bonner, Travis Dunlop, Flavian Vasile, and Alexandros Karatzoglou. 2018. RecoGym: A Reinforcement Learning Environment for the problem of Product Recommendation in Online Advertising. ArXiv , Vol. abs\/1808.00720 (2018)."},{"volume-title":"ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems.","author":"Kenneth","key":"e_1_3_2_1_56_1","unstructured":"Kenneth A. Ross and Yehoshua Sagiv. 1992. Monotonic aggregation in deductive databases . In ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems. Kenneth A. Ross and Yehoshua Sagiv. 1992. Monotonic aggregation in deductive databases. In ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems."},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1145\/3531146.3533129"},{"key":"e_1_3_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.3233\/SHTI220497"},{"key":"e_1_3_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.1145\/3183713.3183735"},{"key":"e_1_3_2_1_60_1","volume-title":"Smith and Lex Beattie","author":"Jessie","year":"2022","unstructured":"Jessie J. Smith and Lex Beattie . 2022 . RecSys Fairness Metrics: Many to Use But Which One To Choose? ArXiv , Vol. abs\/ 2209 .04011 (2022). Jessie J. Smith and Lex Beattie. 2022. RecSys Fairness Metrics: Many to Use But Which One To Choose? ArXiv , Vol. abs\/2209.04011 (2022)."},{"key":"e_1_3_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2007.367935"},{"key":"e_1_3_2_1_62_1","volume-title":"Proceedings of the EDBT Conference.","author":"Stoyanovich Julia","year":"2018","unstructured":"Julia Stoyanovich , Ke Yang , and HV Jagadish . 2018 . Online set selection with fairness and diversity constraints . In Proceedings of the EDBT Conference. Julia Stoyanovich, Ke Yang, and HV Jagadish. 2018. Online set selection with fairness and diversity constraints. In Proceedings of the EDBT Conference."},{"key":"e_1_3_2_1_63_1","doi-asserted-by":"publisher","DOI":"10.5555\/1083592.1083666"},{"key":"e_1_3_2_1_64_1","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2288-5-26"},{"key":"e_1_3_2_1_65_1","doi-asserted-by":"crossref","unstructured":"Hongning Wang Yue Lu and ChengXiang Zhai. 2011. Latent aspect rating analysis without aspect keyword supervision. In Knowledge Discovery and Data Mining.  Hongning Wang Yue Lu and ChengXiang Zhai. 2011. Latent aspect rating analysis without aspect keyword supervision. In Knowledge Discovery and Data Mining.","DOI":"10.1145\/2020408.2020505"},{"key":"e_1_3_2_1_66_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449799"},{"key":"e_1_3_2_1_67_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10619-014-7156-8"},{"key":"e_1_3_2_1_68_1","volume-title":"The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients. Expert systems with applications","author":"Yeh Cheng","year":"2009","unstructured":"I- Cheng Yeh and Che-hui Lien. 2009. The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients. Expert systems with applications , Vol. 36 , 2 ( 2009 ), 2473--2480. I-Cheng Yeh and Che-hui Lien. 2009. The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients. Expert systems with applications , Vol. 36, 2 (2009), 2473--2480."},{"key":"e_1_3_2_1_69_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2008.4497571"},{"key":"e_1_3_2_1_70_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10844-012-0208-5"},{"key":"e_1_3_2_1_71_1","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132938"},{"key":"e_1_3_2_1_72_1","volume-title":"FairSearch: A Tool For Fairness in Ranked Search Results. Companion Proceedings of the Web Conference 2020","author":"Zehlike Meike","year":"2019","unstructured":"Meike Zehlike , Tom S\u00fchr , Carlos Castillo , and Ivan Kitanovski . 2019 . FairSearch: A Tool For Fairness in Ranked Search Results. Companion Proceedings of the Web Conference 2020 (2019). Meike Zehlike, Tom S\u00fchr, Carlos Castillo, and Ivan Kitanovski. 2019. FairSearch: A Tool For Fairness in Ranked Search Results. Companion Proceedings of the Web Conference 2020 (2019)."},{"key":"e_1_3_2_1_73_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-32049-6_5"},{"key":"e_1_3_2_1_74_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00778-009-0162-1"},{"key":"e_1_3_2_1_75_1","doi-asserted-by":"publisher","DOI":"10.1145\/3298689.3346997"},{"key":"e_1_3_2_1_76_1","doi-asserted-by":"publisher","DOI":"10.14778\/3364324.3364327"}],"event":{"name":"CIKM '23: The 32nd ACM International Conference on Information and Knowledge Management","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGIR ACM Special Interest Group on Information Retrieval"],"location":"Birmingham United Kingdom","acronym":"CIKM '23"},"container-title":["Proceedings of the 32nd ACM International Conference on Information and Knowledge Management"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3583780.3614874","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3583780.3614874","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3583780.3614874","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:36:57Z","timestamp":1750178217000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3583780.3614874"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,21]]},"references-count":76,"alternative-id":["10.1145\/3583780.3614874","10.1145\/3583780"],"URL":"https:\/\/doi.org\/10.1145\/3583780.3614874","relation":{},"subject":[],"published":{"date-parts":[[2023,10,21]]},"assertion":[{"value":"2023-10-21","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}