{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T15:34:10Z","timestamp":1774625650821,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":32,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,1,20]],"date-time":"2020-01-20T00:00:00Z","timestamp":1579478400000},"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":[[2020,1,20]]},"DOI":"10.1145\/3336191.3371855","type":"proceedings-article","created":{"date-parts":[[2020,1,22]],"date-time":"2020-01-22T19:08:16Z","timestamp":1579720096000},"page":"618-626","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":51,"title":["Addressing Marketing Bias in Product Recommendations"],"prefix":"10.1145","author":[{"given":"Mengting","family":"Wan","sequence":"first","affiliation":[{"name":"Airbnb, Inc. &amp; University of California, San Diego, Seattle, WA, USA"}]},{"given":"Jianmo","family":"Ni","sequence":"additional","affiliation":[{"name":"University of California, San Diego, La Jolla, CA, USA"}]},{"given":"Rishabh","family":"Misra","sequence":"additional","affiliation":[{"name":"Twitter, Inc., San Francisco, CA, USA"}]},{"given":"Julian","family":"McAuley","sequence":"additional","affiliation":[{"name":"University of California, San Diego, La Jolla, CA, USA"}]}],"member":"320","published-online":{"date-parts":[[2020,1,22]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"crossref","unstructured":"Himan Abdollahpouri Robin Burke and Bamshad Mobasher. 2017. Controlling popularity bias in learning-to-rank recommendation. In RecSys.  Himan Abdollahpouri Robin Burke and Bamshad Mobasher. 2017. Controlling popularity bias in learning-to-rank recommendation. In RecSys.","DOI":"10.1145\/3109859.3109912"},{"key":"e_1_3_2_1_2_1","unstructured":"Yoshua Bengio and Yann LeCun (Eds.). 2015. ICLR.  Yoshua Bengio and Yann LeCun (Eds.). 2015. ICLR."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"crossref","unstructured":"Alex Beutel Jilin Chen Tulsee Doshi Hai Qian Li Wei Yi Wu Lukasz Heldt Zhe Zhao Lichan Hong Ed H Chi et almbox. 2019 a. Fairness in Recommendation Ranking through Pairwise Comparisons. In KDD.  Alex Beutel Jilin Chen Tulsee Doshi Hai Qian Li Wei Yi Wu Lukasz Heldt Zhe Zhao Lichan Hong Ed H Chi et almbox. 2019 a. Fairness in Recommendation Ranking through Pairwise Comparisons. In KDD.","DOI":"10.1145\/3292500.3330745"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"crossref","unstructured":"Alex Beutel Jilin Chen Tulsee Doshi Hai Qian Allison Woodruff Christine Luu Pierre Kreitmann Jonathan Bischof and Ed H. Chi. 2019 b. Putting Fairness Principles into Practice: Challenges Metrics and Improvements. In AIES.  Alex Beutel Jilin Chen Tulsee Doshi Hai Qian Allison Woodruff Christine Luu Pierre Kreitmann Jonathan Bischof and Ed H. Chi. 2019 b. Putting Fairness Principles into Practice: Challenges Metrics and Improvements. In AIES.","DOI":"10.1145\/3306618.3314234"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1086\/295047"},{"key":"e_1_3_2_1_6_1","volume-title":"Conference on Fairness, Accountability and Transparency.","author":"Burke Robin","year":"2018"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"crossref","unstructured":"Michael D Ekstrand Mucun Tian Mohammed R Imran Kazi Hoda Mehrpouyan and Daniel Kluver. 2018. Exploring author gender in book rating and recommendation. In RecSys.  Michael D Ekstrand Mucun Tian Mohammed R Imran Kazi Hoda Mehrpouyan and Daniel Kluver. 2018. Exploring author gender in book rating and recommendation. In RecSys.","DOI":"10.1145\/3240323.3240373"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"crossref","unstructured":"Brian S Everitt. 1992. The analysis of contingency tables.Chapman and Hall\/CRC.  Brian S Everitt. 1992. The analysis of contingency tables.Chapman and Hall\/CRC.","DOI":"10.1201\/b15072"},{"key":"e_1_3_2_1_9_1","unstructured":"Prem Gopalan Jake M Hofman and David M Blei. 2015. Scalable Recommendation with Hierarchical Poisson Factorization.. In UAI.  Prem Gopalan Jake M Hofman and David M Blei. 2015. Scalable Recommendation with Hierarchical Poisson Factorization.. In UAI."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1080\/02650487.2016.1203556"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1177\/002224296703100405"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1177\/002224376800500107"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"crossref","unstructured":"Jonathan L Herlocker Joseph A Konstan Al Borchers and John Riedl. 1999. An algorithmic framework for performing collaborative filtering. In SIGIR.  Jonathan L Herlocker Joseph A Konstan Al Borchers and John Riedl. 1999. An algorithmic framework for performing collaborative filtering. In SIGIR.","DOI":"10.1145\/312624.312682"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11257-015-9165-3"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"crossref","unstructured":"Thorsten Joachims Adith Swaminathan and Tobias Schnabel. 2017. Unbiased learning-to-rank with biased feedback. In WSDM.  Thorsten Joachims Adith Swaminathan and Tobias Schnabel. 2017. Unbiased learning-to-rank with biased feedback. In WSDM.","DOI":"10.1145\/3018661.3018699"},{"key":"e_1_3_2_1_16_1","unstructured":"David G Kleinbaum Lawrence L Kupper Keith E Muller and Azhar Nizam. 1988. Applied regression analysis and other multivariable methods. Vol. 601. Duxbury Press Belmont CA.  David G Kleinbaum Lawrence L Kupper Keith E Muller and Azhar Nizam. 1988. Applied regression analysis and other multivariable methods. Vol. 601. Duxbury Press Belmont CA."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbusres.2006.06.001"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"crossref","unstructured":"Solomon Kullback and Richard A Leibler. 1951. On information and sufficiency. The annals of mathematical statistics Vol. 22 1 (1951) 79--86.  Solomon Kullback and Richard A Leibler. 1951. On information and sufficiency. The annals of mathematical statistics Vol. 22 1 (1951) 79--86.","DOI":"10.1214\/aoms\/1177729694"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"crossref","unstructured":"Greg Linden Brent Smith and Jeremy York. 2003. Amazon.com recommendations: Item-to-item collaborative filtering. IEEE Internet computing 1 (2003) 76--80.  Greg Linden Brent Smith and Jeremy York. 2003. Amazon.com recommendations: Item-to-item collaborative filtering. IEEE Internet computing 1 (2003) 76--80.","DOI":"10.1109\/MIC.2003.1167344"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/0167-4870(88)90029-3"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"crossref","unstructured":"Rishabh Mehrotra James McInerney Hugues Bouchard Mounia Lalmas and Fernando Diaz. 2018. Towards a fair marketplace: Counterfactual evaluation of the trade-off between relevance fairness & satisfaction in recommendation systems. In CIKM.  Rishabh Mehrotra James McInerney Hugues Bouchard Mounia Lalmas and Fernando Diaz. 2018. Towards a fair marketplace: Counterfactual evaluation of the trade-off between relevance fairness & satisfaction in recommendation systems. In CIKM.","DOI":"10.1145\/3269206.3272027"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"crossref","unstructured":"Rishabh Misra Mengting Wan and Julian McAuley. 2018. Decomposing fit semantics for product size recommendation in metric spaces. In RecSys.  Rishabh Misra Mengting Wan and Julian McAuley. 2018. Decomposing fit semantics for product size recommendation in metric spaces. In RecSys.","DOI":"10.1145\/3240323.3240398"},{"key":"e_1_3_2_1_24_1","unstructured":"Jianmo Ni Jiacheng Li and Julian McAuley. 2019. Justifying Recommendations using Distantly-Labeled Reviews and Fine-Grained Aspects. In EMNLP.  Jianmo Ni Jiacheng Li and Julian McAuley. 2019. Justifying Recommendations using Distantly-Labeled Reviews and Fine-Grained Aspects. In EMNLP."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"crossref","unstructured":"Badrul Munir Sarwar George Karypis Joseph A Konstan John Riedl et almbox. 2001. Item-based collaborative filtering recommendation algorithms. In WWW.  Badrul Munir Sarwar George Karypis Joseph A Konstan John Riedl et almbox. 2001. Item-based collaborative filtering recommendation algorithms. In WWW.","DOI":"10.1145\/371920.372071"},{"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.  Tobias Schnabel Adith Swaminathan Ashudeep Singh Navin Chandak and Thorsten Joachims. 2016. Recommendations as Treatments: Debiasing Learning and Evaluation. In ICML."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1086\/208924"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1177\/0092070397253004"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"crossref","unstructured":"Longqi Yang Yin Cui Yuan Xuan Chenyang Wang Serge Belongie and Deborah Estrin. 2018. Unbiased offline recommender evaluation for missing-not-at-random implicit feedback. In RecSys.  Longqi Yang Yin Cui Yuan Xuan Chenyang Wang Serge Belongie and Deborah Estrin. 2018. Unbiased offline recommender evaluation for missing-not-at-random implicit feedback. In RecSys.","DOI":"10.1145\/3240323.3240355"},{"key":"e_1_3_2_1_30_1","unstructured":"Sirui Yao and Bert Huang. 2017. Beyond parity: Fairness objectives for collaborative filtering. In NeurIPS.  Sirui Yao and Bert Huang. 2017. Beyond parity: Fairness objectives for collaborative filtering. In NeurIPS."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"crossref","unstructured":"Xiaoying Zhang Junzhou Zhao and John Lui. 2017. Modeling the assimilation-contrast effects in online product rating systems: Debiasing and recommendations. In RecSys.  Xiaoying Zhang Junzhou Zhao and John Lui. 2017. Modeling the assimilation-contrast effects in online product rating systems: Debiasing and recommendations. In RecSys.","DOI":"10.1145\/3109859.3109885"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"crossref","unstructured":"Ziwei Zhu Xia Hu and James Caverlee. 2018. Fairness-aware tensor-based recommendation. In CIKM.  Ziwei Zhu Xia Hu and James Caverlee. 2018. Fairness-aware tensor-based recommendation. In CIKM.","DOI":"10.1145\/3269206.3271795"}],"event":{"name":"WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining","location":"Houston TX USA","acronym":"WSDM '20","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data","SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 13th International Conference on Web Search and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3336191.3371855","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3336191.3371855","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:23:14Z","timestamp":1750202594000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3336191.3371855"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,1,20]]},"references-count":32,"alternative-id":["10.1145\/3336191.3371855","10.1145\/3336191"],"URL":"https:\/\/doi.org\/10.1145\/3336191.3371855","relation":{},"subject":[],"published":{"date-parts":[[2020,1,20]]},"assertion":[{"value":"2020-01-22","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}