{"id":"https://openalex.org/W3155850838","doi":"https://doi.org/10.1145/3404835.3462892","title":"Counterfactual Reward Modification for Streaming Recommendation with Delayed Feedback","display_name":"Counterfactual Reward Modification for Streaming Recommendation with Delayed Feedback","publication_year":2021,"publication_date":"2021-07-11","ids":{"openalex":"https://openalex.org/W3155850838","doi":"https://doi.org/10.1145/3404835.3462892","mag":"3155850838"},"language":"en","primary_location":{"id":"doi:10.1145/3404835.3462892","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3404835.3462892","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"type":"article","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/A5101939409","display_name":"Xiao Zhang","orcid":"https://orcid.org/0000-0003-2107-2057"},"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":"Xiao Zhang","raw_affiliation_strings":["Renmin University of China & Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Renmin University of China & Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028609507","display_name":"Haonan Jia","orcid":"https://orcid.org/0000-0003-3502-1453"},"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":"Haonan Jia","raw_affiliation_strings":["Beijing Key Laboratory of Big Data Management and Analysis Methods & Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Big Data Management and Analysis Methods & Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076885058","display_name":"Hanjing Su","orcid":"https://orcid.org/0000-0003-3317-2303"},"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":"Hanjing Su","raw_affiliation_strings":["Tencent Inc., Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tencent Inc., Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026622910","display_name":"Wenhan Wang","orcid":"https://orcid.org/0000-0001-7178-8286"},"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":"Wenhan Wang","raw_affiliation_strings":["Tencent Inc., Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tencent Inc., Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020766468","display_name":"Jun Xu","orcid":"https://orcid.org/0000-0001-7170-111X"},"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":"Jun Xu","raw_affiliation_strings":["Renmin University of China & Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Renmin University of China & Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025631695","display_name":"Ji-Rong Wen","orcid":"https://orcid.org/0000-0002-9777-9676"},"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":"Ji-Rong Wen","raw_affiliation_strings":["Renmin University of China & Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Renmin University of China & Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101939409"],"corresponding_institution_ids":["https://openalex.org/I78988378"],"apc_list":null,"apc_paid":null,"fwci":7.1454,"has_fulltext":false,"cited_by_count":55,"citation_normalized_percentile":{"value":0.97371136,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"41","last_page":"50"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":1.0,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9890999794006348,"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/T10603","display_name":"Smart Grid Energy Management","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.934097409248352},{"id":"https://openalex.org/keywords/regret","display_name":"Regret","score":0.8868436217308044},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8050471544265747},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.6942961812019348},{"id":"https://openalex.org/keywords/thompson-sampling","display_name":"Thompson sampling","score":0.5852939486503601},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5342311859130859},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5175966024398804},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4594387412071228}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.934097409248352},{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.8868436217308044},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8050471544265747},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.6942961812019348},{"id":"https://openalex.org/C73602740","wikidata":"https://www.wikidata.org/wiki/Q7795822","display_name":"Thompson sampling","level":3,"score":0.5852939486503601},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5342311859130859},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5175966024398804},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4594387412071228},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3404835.3462892","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3404835.3462892","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7900000214576721,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W189742998","https://openalex.org/W1487320471","https://openalex.org/W1583837637","https://openalex.org/W1835900096","https://openalex.org/W1958090791","https://openalex.org/W2021866613","https://openalex.org/W2049934117","https://openalex.org/W2076618162","https://openalex.org/W2103715332","https://openalex.org/W2108114251","https://openalex.org/W2112420033","https://openalex.org/W2117864026","https://openalex.org/W2122124659","https://openalex.org/W2150713082","https://openalex.org/W2159566498","https://openalex.org/W2188353343","https://openalex.org/W2494566063","https://openalex.org/W2604738573","https://openalex.org/W2607662938","https://openalex.org/W2730527299","https://openalex.org/W2767807341","https://openalex.org/W2785978487","https://openalex.org/W2794526504","https://openalex.org/W2796700885","https://openalex.org/W2799117791","https://openalex.org/W2809291355","https://openalex.org/W2928820257","https://openalex.org/W2944832664","https://openalex.org/W2946399799","https://openalex.org/W2950382198","https://openalex.org/W2962989965","https://openalex.org/W2970231103","https://openalex.org/W2971346467","https://openalex.org/W2973198305","https://openalex.org/W2977606681","https://openalex.org/W2999122685","https://openalex.org/W3003609932","https://openalex.org/W3004726539","https://openalex.org/W3004901471","https://openalex.org/W3006992011","https://openalex.org/W3007931495","https://openalex.org/W3009804075","https://openalex.org/W3015271280","https://openalex.org/W3017342111","https://openalex.org/W3027316409","https://openalex.org/W3035466949","https://openalex.org/W3038664881","https://openalex.org/W3046434636","https://openalex.org/W3100085543","https://openalex.org/W3104881842","https://openalex.org/W3174606363","https://openalex.org/W4288280739","https://openalex.org/W4301256072"],"related_works":["https://openalex.org/W1983202944","https://openalex.org/W2132624896","https://openalex.org/W2802467175","https://openalex.org/W2022564137","https://openalex.org/W2035984254","https://openalex.org/W4291127980","https://openalex.org/W2118206667","https://openalex.org/W633344313","https://openalex.org/W3108185025","https://openalex.org/W1850547517"],"abstract_inverted_index":{"The":[0,38],"user":[1,15,136],"feedbacks":[2,16,40,95,100,137,195],"could":[3],"be":[4,71,81],"delayed":[5,32,39,156,178],"in":[6,107,109],"many":[7],"streaming":[8,66,153],"recommendation":[9,46,67,141,154,214],"scenarios.":[10],"As":[11],"an":[12],"example,":[13],"the":[14,23,27,31,35,59,65,76,93,99,110,115,118,135,140,152,175,193,198,203,216,223,230,246,253],"to":[17,56,70,80,133,191],"a":[18,42,102,126,159,169,184,206,235,250,257],"recommended":[19],"coupon":[20],"consist":[21],"of":[22,44,117,161,177],"immediate":[24],"feedback":[25,33,157],"on":[26,34,101,202,249],"click":[28],"event":[29],"and":[30,75,113,128,138,165,196,229,256],"resultant":[36],"conversion.":[37],"pose":[41],"challenge":[43,60],"training":[45,77,111],"models":[47,68,166],"using":[48],"instances":[49,78],"with":[50,147,155,168,174],"incomplete":[51],"labels.":[52],"When":[53],"being":[54],"applied":[55],"real":[57],"products,":[58],"becomes":[61],"more":[62],"severe":[63],"as":[64,158],"need":[69,79],"retrained":[72],"very":[73,84],"frequently":[74],"collected":[82],"over":[83],"short":[85],"time":[86],"scales.":[87],"Existing":[88],"approaches":[89],"either":[90],"simply":[91],"ignore":[92],"unobserved":[94],"or":[96],"heuristically":[97],"adjust":[98],"static":[103],"instance":[104],"set,":[105],"resulting":[106],"biases":[108],"data":[112],"hurting":[114],"accuracy":[116],"learned":[119,210,231],"recommenders.":[120],"In":[121],"this":[122],"paper,":[123],"we":[124],"propose":[125],"novel":[127],"theoretic":[129],"sound":[130],"counterfactual":[131,185],"approach":[132],"adjusting":[134],"learning":[139],"models,":[142],"called":[143],"CBDF":[144,150,243],"(Counterfactual":[145],"Bandit":[146],"Delayed":[148],"Feedback).":[149],"formulates":[151],"problem":[160],"sequential":[162],"decision":[163],"making":[164],"it":[167],"batched":[170,207],"bandit.":[171],"To":[172],"deal":[173],"issue":[176],"feedback,":[179],"at":[180,215],"each":[181],"iteration":[182],"(episode),":[183],"importance":[186],"sampling":[187],"model":[188],"is":[189,209],"employed":[190],"re-weight":[192],"original":[194],"generate":[197],"modified":[199,204,224],"rewards.":[200],"Based":[201],"rewards,":[205],"bandit":[208,232],"for":[211],"conducting":[212],"online":[213],"next":[217],"iteration.":[218],"Theoretical":[219],"analysis":[220],"showed":[221],"that":[222,242],"rewards":[225],"are":[226],"statistically":[227],"unbiased,":[228],"policy":[233],"enjoys":[234],"sub-linear":[236],"regret":[237],"bound.":[238],"Experimental":[239],"results":[240],"demonstrated":[241],"can":[244],"outperform":[245],"state-of-the-art":[247],"baselines":[248],"synthetic":[251],"dataset,":[252,255],"Criteo":[254],"dataset":[258],"from":[259],"Tencent's":[260],"WeChat":[261],"app.":[262]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":17},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":7}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}