{"id":"https://openalex.org/W3210703899","doi":"https://doi.org/10.1145/3459637.3482052","title":"Adversarial Learning for Incentive Optimization in Mobile Payment Marketing","display_name":"Adversarial Learning for Incentive Optimization in Mobile Payment Marketing","publication_year":2021,"publication_date":"2021-10-26","ids":{"openalex":"https://openalex.org/W3210703899","doi":"https://doi.org/10.1145/3459637.3482052","mag":"3210703899"},"language":"en","primary_location":{"id":"doi:10.1145/3459637.3482052","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482052","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018586255","display_name":"Xuanying Chen","orcid":"https://orcid.org/0009-0003-2300-3407"},"institutions":[{"id":"https://openalex.org/I4210090985","display_name":"Zhejiang Financial College","ror":"https://ror.org/00deghz86","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210090985"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuanying Chen","raw_affiliation_strings":["Ant Financial Services Group, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ant Financial Services Group, Hangzhou, China","institution_ids":["https://openalex.org/I4210090985"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101641280","display_name":"Zhining Liu","orcid":"https://orcid.org/0000-0003-1828-2109"},"institutions":[{"id":"https://openalex.org/I4210090985","display_name":"Zhejiang Financial College","ror":"https://ror.org/00deghz86","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210090985"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhining Liu","raw_affiliation_strings":["Ant Financial Services Group, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ant Financial Services Group, Hangzhou, China","institution_ids":["https://openalex.org/I4210090985"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103217890","display_name":"Li Yu","orcid":"https://orcid.org/0000-0003-1370-1909"},"institutions":[{"id":"https://openalex.org/I4210090985","display_name":"Zhejiang Financial College","ror":"https://ror.org/00deghz86","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210090985"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Yu","raw_affiliation_strings":["Ant Financial Services Group, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ant Financial Services Group, Hangzhou, China","institution_ids":["https://openalex.org/I4210090985"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100444231","display_name":"Sen Li","orcid":"https://orcid.org/0000-0001-7747-4253"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sen Li","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058735109","display_name":"Lihong Gu","orcid":"https://orcid.org/0000-0002-0706-3448"},"institutions":[{"id":"https://openalex.org/I4210090985","display_name":"Zhejiang Financial College","ror":"https://ror.org/00deghz86","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210090985"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lihong Gu","raw_affiliation_strings":["Ant Financial Services Group, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ant Financial Services Group, Hangzhou, China","institution_ids":["https://openalex.org/I4210090985"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059787539","display_name":"Xiaodong Zeng","orcid":"https://orcid.org/0000-0001-7638-5443"},"institutions":[{"id":"https://openalex.org/I4210090985","display_name":"Zhejiang Financial College","ror":"https://ror.org/00deghz86","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210090985"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaodong Zeng","raw_affiliation_strings":["Ant Financial Services Group, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ant Financial Services Group, Hangzhou, China","institution_ids":["https://openalex.org/I4210090985"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046875626","display_name":"Yize Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210090985","display_name":"Zhejiang Financial College","ror":"https://ror.org/00deghz86","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210090985"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yize Tan","raw_affiliation_strings":["Ant Financial Services Group, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ant Financial Services Group, Hangzhou, China","institution_ids":["https://openalex.org/I4210090985"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053242349","display_name":"Jinjie Gu","orcid":"https://orcid.org/0000-0001-7596-4945"},"institutions":[{"id":"https://openalex.org/I4210090985","display_name":"Zhejiang Financial College","ror":"https://ror.org/00deghz86","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210090985"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinjie Gu","raw_affiliation_strings":["Ant Financial Services Group, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ant Financial Services Group, Hangzhou, China","institution_ids":["https://openalex.org/I4210090985"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2940","last_page":"2944"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9889000058174133,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7406613826751709},{"id":"https://openalex.org/keywords/incentive","display_name":"Incentive","score":0.6658503413200378},{"id":"https://openalex.org/keywords/payment","display_name":"Payment","score":0.5693964958190918},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4719373881816864},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.462103009223938},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4518425762653351},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.4404260218143463},{"id":"https://openalex.org/keywords/linear-programming","display_name":"Linear programming","score":0.4389092028141022},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.4116630256175995},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3302925229072571},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29189014434814453},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.13538551330566406},{"id":"https://openalex.org/keywords/microeconomics","display_name":"Microeconomics","score":0.12426963448524475},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.09229886531829834}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7406613826751709},{"id":"https://openalex.org/C29122968","wikidata":"https://www.wikidata.org/wiki/Q1414816","display_name":"Incentive","level":2,"score":0.6658503413200378},{"id":"https://openalex.org/C145097563","wikidata":"https://www.wikidata.org/wiki/Q1148747","display_name":"Payment","level":2,"score":0.5693964958190918},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4719373881816864},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.462103009223938},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4518425762653351},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.4404260218143463},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.4389092028141022},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.4116630256175995},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3302925229072571},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29189014434814453},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.13538551330566406},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.12426963448524475},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.09229886531829834},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3459637.3482052","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482052","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1906002163","https://openalex.org/W2099471712","https://openalex.org/W2141843793","https://openalex.org/W2150291618","https://openalex.org/W2174890733","https://openalex.org/W2304640842","https://openalex.org/W2396906324","https://openalex.org/W2584924584","https://openalex.org/W2604584762","https://openalex.org/W2629213068","https://openalex.org/W2743316574","https://openalex.org/W2808956106","https://openalex.org/W2809366716","https://openalex.org/W2963052087","https://openalex.org/W2963332753","https://openalex.org/W2984589663","https://openalex.org/W2987962448","https://openalex.org/W3103310105"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4310988119","https://openalex.org/W2108936692","https://openalex.org/W4317927411"],"abstract_inverted_index":{"Many":[0],"payment":[1,44],"platforms":[2],"hold":[3],"large-scale":[4],"marketing":[5,172],"campaigns,":[6],"which":[7],"allocate":[8],"incentives":[9],"to":[10,13,39,53,131,140],"encourage":[11],"users":[12],"pay":[14],"through":[15],"their":[16],"applications.":[17],"To":[18,105],"maximize":[19],"the":[20,41,55,60,67,72,84,87,92,98,101,119,142,162,165],"return":[21],"on":[22],"investment,":[23],"incentive":[24,57],"allocations":[25],"are":[26],"commonly":[27],"solved":[28],"in":[29,66,169],"a":[30,35,47,78,111,127,170],"two-stage":[31],"procedure.":[32],"After":[33],"training":[34,68],"response":[36,88],"estimation":[37],"model":[38,89,135],"estimate":[40],"users'":[42],"mobile":[43],"probabilities":[45],"(MPP),":[46],"linear":[48,93],"programming":[49,94],"process":[50],"is":[51],"applied":[52],"obtain":[54],"optimal":[56],"allocation.":[58],"However,":[59],"large":[61],"amount":[62],"of":[63,86,100,122,164],"biased":[64,74,79],"data":[65,124],"set,":[69],"generated":[70],"by":[71],"previous":[73],"allocation":[75,103,129,167],"policy,":[76],"causes":[77],"estimation.":[80],"This":[81],"bias":[82,112,143],"deteriorates":[83],"performance":[85,99,163],"and":[90,136,148,159],"misleads":[91],"process,":[95],"dramatically":[96],"degrading":[97],"resulting":[102,166],"policy.":[104],"overcome":[106],"this":[107],"obstacle,":[108],"we":[109],"propose":[110],"correction":[113],"adversarial":[114,145],"network.":[115],"Our":[116],"method":[117,155],"leverages":[118],"small":[120],"set":[121],"unbiased":[123,134],"obtained":[125],"under":[126],"full-randomized":[128],"policy":[130,168],"train":[132],"an":[133],"then":[137],"uses":[138],"it":[139],"reduce":[141],"with":[144],"learning.":[146],"Offline":[147],"online":[149],"experimental":[150],"results":[151],"demonstrate":[152],"that":[153],"our":[154],"outperforms":[156],"state-of-the-art":[157],"approaches":[158],"significantly":[160],"improves":[161],"real-world":[171],"campaign.":[173]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}