{"id":"https://openalex.org/W4403219678","doi":"https://doi.org/10.1145/3640457.3688147","title":"End-to-End Cost-Effective Incentive Recommendation under Budget Constraint with Uplift Modeling","display_name":"End-to-End Cost-Effective Incentive Recommendation under Budget Constraint with Uplift Modeling","publication_year":2024,"publication_date":"2024-10-08","ids":{"openalex":"https://openalex.org/W4403219678","doi":"https://doi.org/10.1145/3640457.3688147"},"language":"en","primary_location":{"id":"doi:10.1145/3640457.3688147","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3640457.3688147","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3640457.3688147","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"18th ACM Conference on Recommender Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3640457.3688147","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087242567","display_name":"Zexu Sun","orcid":"https://orcid.org/0000-0002-6727-6242"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zexu Sun","raw_affiliation_strings":["Gaoling School of Artificial Intelligence, Renmin University of China, China"],"affiliations":[{"raw_affiliation_string":"Gaoling School of Artificial Intelligence, Renmin University of China, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101551028","display_name":"Hao Yang","orcid":"https://orcid.org/0009-0008-5365-897X"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Yang","raw_affiliation_strings":["Gaoling School of Artificial Intelligence, Renmin University of China, China"],"affiliations":[{"raw_affiliation_string":"Gaoling School of Artificial Intelligence, Renmin University of China, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003106644","display_name":"Dugang Liu","orcid":"https://orcid.org/0000-0003-3612-709X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dugang Liu","raw_affiliation_strings":["Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), China"],"affiliations":[{"raw_affiliation_string":"Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029446856","display_name":"Yunpeng Weng","orcid":"https://orcid.org/0000-0001-7593-2169"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunpeng Weng","raw_affiliation_strings":["FiT, Tencent, China"],"affiliations":[{"raw_affiliation_string":"FiT, Tencent, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071989106","display_name":"Xing Tang","orcid":"https://orcid.org/0000-0003-4360-0754"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xing Tang","raw_affiliation_strings":["FiT, Tencent, China"],"affiliations":[{"raw_affiliation_string":"FiT, Tencent, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083350101","display_name":"Xiuqiang He","orcid":"https://orcid.org/0000-0002-4115-8205"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiuqiang He","raw_affiliation_strings":["FiT,Tencent, China"],"affiliations":[{"raw_affiliation_string":"FiT,Tencent, China","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5087242567"],"corresponding_institution_ids":["https://openalex.org/I78988378"],"apc_list":null,"apc_paid":null,"fwci":1.0348,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.83020154,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"560","last_page":"569"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10328","display_name":"Supply Chain and Inventory Management","score":0.9909999966621399,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"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/T10328","display_name":"Supply Chain and Inventory Management","score":0.9909999966621399,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"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/T11182","display_name":"Auction Theory and Applications","score":0.9815999865531921,"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"}},{"id":"https://openalex.org/T10632","display_name":"Housing Market and Economics","score":0.9585000276565552,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/incentive","display_name":"Incentive","score":0.6779274940490723},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5995606780052185},{"id":"https://openalex.org/keywords/budget-constraint","display_name":"Budget constraint","score":0.580328106880188},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.5101919174194336},{"id":"https://openalex.org/keywords/operations-research","display_name":"Operations research","score":0.3465534448623657},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.18857252597808838},{"id":"https://openalex.org/keywords/microeconomics","display_name":"Microeconomics","score":0.16547244787216187},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14009538292884827}],"concepts":[{"id":"https://openalex.org/C29122968","wikidata":"https://www.wikidata.org/wiki/Q1414816","display_name":"Incentive","level":2,"score":0.6779274940490723},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5995606780052185},{"id":"https://openalex.org/C8505890","wikidata":"https://www.wikidata.org/wiki/Q605095","display_name":"Budget constraint","level":2,"score":0.580328106880188},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.5101919174194336},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.3465534448623657},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.18857252597808838},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.16547244787216187},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14009538292884827},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3640457.3688147","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3640457.3688147","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3640457.3688147","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"18th ACM Conference on Recommender Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3640457.3688147","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3640457.3688147","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3640457.3688147","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"18th ACM Conference on Recommender Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4297194486","display_name":null,"funder_award_id":"No.62302310","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4403219678.pdf","grobid_xml":"https://content.openalex.org/works/W4403219678.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1516659296","https://openalex.org/W2042206577","https://openalex.org/W2140899775","https://openalex.org/W2614303240","https://openalex.org/W2619014254","https://openalex.org/W2624816748","https://openalex.org/W2891638642","https://openalex.org/W2949676527","https://openalex.org/W2963052087","https://openalex.org/W2973001878","https://openalex.org/W2988150581","https://openalex.org/W2998229673","https://openalex.org/W3001202326","https://openalex.org/W3049690396","https://openalex.org/W3097152630","https://openalex.org/W3106521244","https://openalex.org/W3154617266","https://openalex.org/W3171671666","https://openalex.org/W3197320891","https://openalex.org/W3204398858","https://openalex.org/W4206614441","https://openalex.org/W4207029607","https://openalex.org/W4220930599","https://openalex.org/W4283808933","https://openalex.org/W4288079506","https://openalex.org/W4382239939","https://openalex.org/W4385562507"],"related_works":["https://openalex.org/W83893804","https://openalex.org/W2178649091","https://openalex.org/W2353238953","https://openalex.org/W2496037054","https://openalex.org/W2024895661","https://openalex.org/W2390883384","https://openalex.org/W2054108430","https://openalex.org/W3123594720","https://openalex.org/W2360283705","https://openalex.org/W2015936298"],"abstract_inverted_index":{"In":[0,207],"modern":[1],"online":[2,42,119],"platforms,":[3],"incentives":[4,33],"(e.g.,":[5],"discounts,":[6],"bonus)":[7],"are":[8],"essential":[9],"factors":[10],"that":[11,261],"enhance":[12],"user":[13],"engagement":[14],"and":[15,132,202,231,256],"increase":[16],"platform":[17],"revenue.":[18],"Over":[19],"recent":[20],"years,":[21],"uplift":[22,165,199,209],"modeling":[23],"has":[24],"been":[25],"introduced":[26],"as":[27,57,134,239],"a":[28,96,127,178,240],"strategic":[29],"approach":[30],"to":[31,34,69,77,155,216,268],"assign":[32],"individual":[35],"customers.":[36],"Especially":[37],"in":[38,86,118,149,244],"many":[39],"real-world":[40],"applications,":[41],"platforms":[43],"can":[44,54],"only":[45],"incentivize":[46],"customers":[47],"with":[48,104,224],"specific":[49],"budget":[50,92,170,188],"constraints.":[51],"This":[52],"problem":[53,61,94],"be":[55,130],"reformulated":[56],"the":[58,71,79,91,105,115,122,135,145,156,159,164,168,187,198,203,208,218,225,245],"multi-choice":[59],"knapsack":[60],"(MCKP).":[62],"The":[63,109],"objective":[64],"of":[65,126,158,194],"this":[66,87,100],"optimization":[67],"is":[68,102,140],"select":[70],"optimal":[72],"incentive":[73,136,160],"for":[74,163],"each":[75],"customer":[76,128],"maximize":[78],"return":[80],"on":[81,254],"investment":[82],"(ROI).":[83],"Recent":[84],"works":[85],"field":[88],"frequently":[89],"tackle":[90],"allocation":[93,152,205,247,265],"using":[95],"two-stage":[97,270],"approach.":[98],"However,":[99],"solution":[101],"confronted":[103],"following":[106],"challenges:":[107],"(1)":[108],"causal":[110],"inference":[111],"methods":[112,192],"often":[113],"ignore":[114],"domain":[116,227],"knowledge":[117],"marketing,":[120],"where":[121],"expected":[123],"response":[124],"curve":[125],"should":[129],"monotonic":[131,230],"smooth":[133],"increases.":[137],"(2)":[138],"There":[139],"an":[141],"optimality":[142],"gap":[143],"between":[144,221],"two":[146,195],"stages,":[147],"resulting":[148],"inferior":[150],"sub-optimal":[151],"performance":[153,266],"due":[154],"loss":[157],"recommendation":[161],"information":[162],"prediction":[166,200,210,214],"under":[167,186],"limited":[169],"constraint.":[171,189],"To":[172],"address":[173],"these":[174],"challenges,":[175],"we":[176,212,250],"propose":[177],"novel":[179],"End-to-End":[180],"Cost-Effective":[181],"Incentive":[182],"Recommendation":[183],"(E3IR)":[184],"model":[185],"Specifically,":[190],"our":[191,262],"consist":[193],"modules,":[196],"i.e.,":[197],"module":[201],"differentiable":[204,241,246],"module.":[206,248],"module,":[211],"construct":[213],"heads":[215],"capture":[217],"incremental":[219],"improvement":[220],"adjacent":[222],"treatments":[223],"marketing":[226],"constraints":[228],"(i.e.,":[229],"smooth).":[232],"We":[233],"incorporate":[234],"integer":[235],"linear":[236],"programming":[237],"(ILP)":[238],"layer":[242],"input":[243],"Furthermore,":[249],"conduct":[251],"extensive":[252],"experiments":[253],"public":[255],"real":[257],"product":[258],"datasets,":[259],"demonstrating":[260],"E3IR":[263],"improves":[264],"compared":[267],"existing":[269],"approaches.":[271]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}