{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T03:58:53Z","timestamp":1763179133954,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":28,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,7,25]],"date-time":"2019-07-25T00:00:00Z","timestamp":1564012800000},"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":[[2019,7,25]]},"DOI":"10.1145\/3292500.3330768","type":"proceedings-article","created":{"date-parts":[[2019,7,26]],"date-time":"2019-07-26T13:17:26Z","timestamp":1564147046000},"page":"3071-3081","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["TV Advertisement Scheduling by Learning Expert Intentions"],"prefix":"10.1145","author":[{"given":"Yasuhisa","family":"Suzuki","sequence":"first","affiliation":[{"name":"NEC Corporation, Kawasaki, Kanagawa, Japan"}]},{"given":"Wemer M.","family":"Wee","sequence":"additional","affiliation":[{"name":"NEC Corporation, Kawasaki, Kanagawa, Japan"}]},{"given":"Itaru","family":"Nishioka","sequence":"additional","affiliation":[{"name":"NEC Corporation, Kawasaki, Kanagawa, Japan"}]}],"member":"320","published-online":{"date-parts":[[2019,7,25]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015430"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.5555\/767778.769030"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1287\/opre.2017.1705"},{"volume-title":"Proceedings of the 34th International Conference on Machine Learning, ICML 2017. 400--410","year":"2017","author":"B\u00e4rmann Andreas","key":"e_1_3_2_1_4_1"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1287\/opre.1040.0119"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1287\/inte.32.1.47.19"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1287\/opre.1030.0083"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2018.02.045"},{"volume-title":"Annual Conference on Neural Information Processing Systems, NeurIPS","year":"2018","author":"Dong Chaosheng","key":"e_1_3_2_1_9_1"},{"volume-title":"Inferring Parameters Through Inverse Multiobjective Optimization. arXiv preprint arXiv:1808.00935","year":"2018","author":"Dong Chaosheng","key":"e_1_3_2_1_10_1"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-017-1216-6"},{"edition":"4","volume-title":"Cluster Analysis","author":"Everitt Brian S.","key":"e_1_3_2_1_12_1"},{"volume-title":"Reibstein","year":"2010","author":"Farris Paul W.","key":"e_1_3_2_1_13_1"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.orl.2018.03.007"},{"key":"e_1_3_2_1_15_1","unstructured":"Dentsu Inc. 2018. Advertising Expenditures in Japan. http:\/\/www.dentsu.com\/knowledgeanddata\/ad_expenditures\/ (Accessed on 05\/15\/2019).  Dentsu Inc. 2018. Advertising Expenditures in Japan. http:\/\/www.dentsu.com\/knowledgeanddata\/ad_expenditures\/ (Accessed on 05\/15\/2019)."},{"volume-title":"Information Theory and Statistical Mechanics. Physical Review 106 (May","year":"1957","author":"Jaynes Edwin T.","key":"e_1_3_2_1_16_1"},{"key":"e_1_3_2_1_17_1","unstructured":"Eric Jones Travis Oliphant Pearu Peterson etal 2001--. SciPy: Open source scientific tools for Python. http:\/\/www.scipy.org\/ (Accessed on 05\/15\/2019).  Eric Jones Travis Oliphant Pearu Peterson et al. 2001--. SciPy: Open source scientific tools for Python. http:\/\/www.scipy.org\/ (Accessed on 05\/15\/2019)."},{"volume-title":"Getting the Deal Through - Advertising and Marketing","year":"2018","author":"Kurnit Rick","key":"e_1_3_2_1_18_1"},{"key":"e_1_3_2_1_19_1","unstructured":"Gurobi Optimization LLC. 2019. Gurobi Optimizer Reference Manual. http:\/\/www.gurobi.com (Accessed on 05\/15\/2019).  Gurobi Optimization LLC. 2019. Gurobi Optimizer Reference Manual. http:\/\/www.gurobi.com (Accessed on 05\/15\/2019)."},{"volume-title":"Proceedings of the Seventeenth International Conference on Machine Learning, ICML","year":"2000","author":"Andrew","key":"e_1_3_2_1_20_1"},{"key":"e_1_3_2_1_21_1","unstructured":"Mark J Panaggio Pak-Wing Fok Ghan S Bhatt Simon Burhoe Michael Capps Christina J Edholm Fadoua El Moustaid Tegan Emerson Star-Lena Estock Nathan Gold Ryan Halabi Madelyn Houser Peter R Kramer Hsuan-Wei Lee Qingxia Li Weiqiang Li Dan Lu Yuzhou Qian Louis F Rossi Deborah Shutt Vicky Chuqiao Yang and Yingxiang Zhou. 2016. Prediction and Optimal Scheduling of Advertisements in Linear Television. arXiv preprint arXiv:1608.07305 (2016).  Mark J Panaggio Pak-Wing Fok Ghan S Bhatt Simon Burhoe Michael Capps Christina J Edholm Fadoua El Moustaid Tegan Emerson Star-Lena Estock Nathan Gold Ryan Halabi Madelyn Houser Peter R Kramer Hsuan-Wei Lee Qingxia Li Weiqiang Li Dan Lu Yuzhou Qian Louis F Rossi Deborah Shutt Vicky Chuqiao Yang and Yingxiang Zhou. 2016. Prediction and Optimal Scheduling of Advertisements in Linear Television. arXiv preprint arXiv:1608.07305 (2016)."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.5555\/1953048.2078195"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1287\/mnsc.2015.2185"},{"volume-title":"Proceedings of the 20th International Joint Conference on Artificial Intelligence, IJCAI 2007. 2586--2591","year":"2007","author":"Ramachandran Deepak","key":"e_1_3_2_1_24_1"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"crossref","unstructured":"Lior Rokach and Oded Maimon. 2005. Clustering Methods. In The Data Mining and Knowledge Discovery Handbook. 321--352.  Lior Rokach and Oded Maimon. 2005. Clustering Methods. In The Data Mining and Knowledge Discovery Handbook. 321--352.","DOI":"10.1007\/0-387-25465-X_15"},{"volume-title":"An overview of gradient descent optimization algorithms. arXiv preprint abs\/1609.04747","year":"2016","author":"Ruder Sebastian","key":"e_1_3_2_1_26_1"},{"volume-title":"Maximum Entropy Deep Inverse Reinforcement Learning. arXiv preprint arXiv:1507.04888","year":"2015","author":"Ondruska Peter","key":"e_1_3_2_1_27_1"},{"volume-title":"Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, AAAI","year":"2008","author":"Ziebart Brian D.","key":"e_1_3_2_1_28_1"}],"event":{"name":"KDD '19: The 25th 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":"Anchorage AK USA","acronym":"KDD '19"},"container-title":["Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3292500.3330768","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3292500.3330768","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T00:57:51Z","timestamp":1750208271000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3292500.3330768"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,25]]},"references-count":28,"alternative-id":["10.1145\/3292500.3330768","10.1145\/3292500"],"URL":"https:\/\/doi.org\/10.1145\/3292500.3330768","relation":{},"subject":[],"published":{"date-parts":[[2019,7,25]]},"assertion":[{"value":"2019-07-25","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}