{"id":"https://openalex.org/W4306316994","doi":"https://doi.org/10.1145/3511808.3557579","title":"Deep Presentation Bias Integrated Framework for CTR Prediction","display_name":"Deep Presentation Bias Integrated Framework for CTR Prediction","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4306316994","doi":"https://doi.org/10.1145/3511808.3557579"},"language":"en","primary_location":{"id":"doi:10.1145/3511808.3557579","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557579","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","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/A5101945411","display_name":"Jianqiang Huang","orcid":"https://orcid.org/0000-0002-4454-7919"},"institutions":[{"id":"https://openalex.org/I4210087373","display_name":"Meizu (China)","ror":"https://ror.org/0067g4302","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210087373"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianqiang Huang","raw_affiliation_strings":["Meituan, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Meituan, Beijing, China","institution_ids":["https://openalex.org/I4210087373"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067855732","display_name":"Xingyuan Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210087373","display_name":"Meizu (China)","ror":"https://ror.org/0067g4302","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210087373"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingyuan Tang","raw_affiliation_strings":["Meituan, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Meituan, Beijing, China","institution_ids":["https://openalex.org/I4210087373"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100407591","display_name":"Zhe Wang","orcid":"https://orcid.org/0000-0001-9727-5569"},"institutions":[{"id":"https://openalex.org/I4210087373","display_name":"Meizu (China)","ror":"https://ror.org/0067g4302","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210087373"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhe Wang","raw_affiliation_strings":["Meituan, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Meituan, Beijing, China","institution_ids":["https://openalex.org/I4210087373"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051277007","display_name":"Shaolin Jia","orcid":null},"institutions":[{"id":"https://openalex.org/I4210087373","display_name":"Meizu (China)","ror":"https://ror.org/0067g4302","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210087373"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaolin Jia","raw_affiliation_strings":["Meituan, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Meituan, Beijing, China","institution_ids":["https://openalex.org/I4210087373"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100567843","display_name":"Yin Bai","orcid":"https://orcid.org/0000-0002-3157-255X"},"institutions":[{"id":"https://openalex.org/I4210087373","display_name":"Meizu (China)","ror":"https://ror.org/0067g4302","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210087373"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yin Bai","raw_affiliation_strings":["Meituan, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Meituan, Beijing, China","institution_ids":["https://openalex.org/I4210087373"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100321247","display_name":"Zhiwei Liu","orcid":"https://orcid.org/0000-0003-1525-1067"},"institutions":[{"id":"https://openalex.org/I4210087373","display_name":"Meizu (China)","ror":"https://ror.org/0067g4302","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210087373"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiwei Liu","raw_affiliation_strings":["Meituan, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Meituan, Beijing, China","institution_ids":["https://openalex.org/I4210087373"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003039093","display_name":"Jia Cheng","orcid":"https://orcid.org/0000-0003-1702-4263"},"institutions":[{"id":"https://openalex.org/I4210087373","display_name":"Meizu (China)","ror":"https://ror.org/0067g4302","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210087373"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jia Cheng","raw_affiliation_strings":["Meituan, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Meituan, Beijing, China","institution_ids":["https://openalex.org/I4210087373"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084801659","display_name":"Jun Lei","orcid":"https://orcid.org/0000-0002-4015-8668"},"institutions":[{"id":"https://openalex.org/I4210087373","display_name":"Meizu (China)","ror":"https://ror.org/0067g4302","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210087373"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Lei","raw_affiliation_strings":["Meituan, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Meituan, Beijing, China","institution_ids":["https://openalex.org/I4210087373"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100456377","display_name":"Yan Zhang","orcid":"https://orcid.org/0000-0003-1585-0801"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Zhang","raw_affiliation_strings":["Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5101945411"],"corresponding_institution_ids":["https://openalex.org/I4210087373"],"apc_list":null,"apc_paid":null,"fwci":0.2913,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.53059745,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"4049","last_page":"4053"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9997000098228455,"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/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9975000023841858,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9933000206947327,"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":0.7814962863922119},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.7504972219467163},{"id":"https://openalex.org/keywords/presentation","display_name":"Presentation (obstetrics)","score":0.7167631387710571},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6730414032936096},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.6475486159324646},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5914753079414368},{"id":"https://openalex.org/keywords/click-through-rate","display_name":"Click-through rate","score":0.5887081027030945},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4687288999557495},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.46820834279060364},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.420899897813797},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4064273238182068}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7814962863922119},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.7504972219467163},{"id":"https://openalex.org/C2777601897","wikidata":"https://www.wikidata.org/wiki/Q3409113","display_name":"Presentation (obstetrics)","level":2,"score":0.7167631387710571},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6730414032936096},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.6475486159324646},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5914753079414368},{"id":"https://openalex.org/C115174607","wikidata":"https://www.wikidata.org/wiki/Q1100934","display_name":"Click-through rate","level":2,"score":0.5887081027030945},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4687288999557495},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.46820834279060364},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.420899897813797},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4064273238182068},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3511808.3557579","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557579","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2141461755","https://openalex.org/W2150291618","https://openalex.org/W2155587858","https://openalex.org/W2340526403","https://openalex.org/W2475334473","https://openalex.org/W2507134384","https://openalex.org/W2610314927","https://openalex.org/W2723293840","https://openalex.org/W2769473018","https://openalex.org/W2793768763","https://openalex.org/W2797400361","https://openalex.org/W2905569957","https://openalex.org/W2912255075","https://openalex.org/W2945772520","https://openalex.org/W2964182926","https://openalex.org/W2972358762","https://openalex.org/W2973172293","https://openalex.org/W3012600133","https://openalex.org/W3047934539","https://openalex.org/W3080386552","https://openalex.org/W3080768030","https://openalex.org/W3088393583","https://openalex.org/W3093519337","https://openalex.org/W3101148092","https://openalex.org/W3104030692","https://openalex.org/W3105712174","https://openalex.org/W3106252282","https://openalex.org/W3115487106"],"related_works":["https://openalex.org/W4387426029","https://openalex.org/W4254162896","https://openalex.org/W4388792380","https://openalex.org/W1477999932","https://openalex.org/W4386731653","https://openalex.org/W2150136235","https://openalex.org/W2053591227","https://openalex.org/W2041353081","https://openalex.org/W2581240705","https://openalex.org/W2568183987"],"abstract_inverted_index":{"In":[0,136],"online":[1,81,246],"advertising,":[2],"click-through":[3],"rate":[4],"(CTR)":[5],"prediction":[6,186],"typically":[7],"utilizes":[8],"click":[9,48,109,124,182],"data":[10],"to":[11,46,66,105,111,133,215,233,255],"train":[12],"models":[13],"for":[14,98,172,207],"estimating":[15,200],"the":[16,26,41,51,74,83,91,108,112,150,159,174,192,195,217,227,235,239,257,260],"probability":[17],"of":[18,29,176,199,238,259],"a":[19,141,252],"user":[20,117,165],"clicking":[21],"on":[22,158],"an":[23,30,221],"item.":[24,209],"However,":[25],"different":[27,47,181,205],"presentations":[28,206],"item,":[31],"including":[32,70],"its":[33],"position":[34,60],"and":[35,44,62,155,168,245],"contextual":[36,156],"items,":[37],"etc.,":[38],"will":[39],"affect":[40],"user's":[42],"attention":[43,65],"lead":[45],"propensities,":[49],"thus":[50],"presentation":[52,68,76,114,151,177,240],"bias":[53,61,69,84,178],"arises.":[54],"Most":[55],"previous":[56],"works":[57],"generally":[58],"consider":[59],"pay":[63],"less":[64],"overall":[67],"context.":[71],"Simultaneously,":[72],"since":[73],"final":[75],"list":[77],"is":[78,87,103,162,197,231],"unreachable":[79],"during":[80],"inference,":[82],"independence":[85,193],"assumption":[86,102],"adopted":[88],"so":[89,225],"that":[90,226],"debiased":[92,128],"relevance":[93,129],"can":[94],"be":[95,131],"directly":[96],"used":[97,214],"ranking.":[99],"But":[100],"this":[101,137],"difficult":[104],"hold":[106],"because":[107],"propensity":[110,125],"item":[113,154,171],"varies":[115],"with":[116,122,191],"intent.":[118],"Therefore,":[119],"predicted":[120,169],"CTR":[121,185],"personalized":[123],"rather":[126],"than":[127],"should":[130],"closer":[132],"real":[134],"CTR.":[135],"work,":[138],"we":[139],"propose":[140],"Deep":[142],"Presentation":[143],"Bias":[144],"Integrated":[145],"Framework":[146],"(DPBIF).":[147],"With":[148],"DPBIF,":[149],"block":[152],"containing":[153],"items":[157],"same":[160],"screen":[161],"introduced":[163],"into":[164,184,220],"behavior":[166],"sequence":[167],"target":[170],"personalizing":[173],"integration":[175],"caused":[179],"by":[180],"propensities":[183],"network.":[187],"While":[188],"avoiding":[189],"modeling":[190],"assumption,":[194],"network":[196],"capable":[198],"multiple":[201,211],"integrated":[202],"CTRs":[203,212],"under":[204],"each":[208],"The":[210],"are":[213,249],"transform":[216],"ranking":[218],"problem":[219,224],"item-to-position":[222],"assignment":[223],"Kuhn-Munkres":[228],"(KM)":[229],"algorithm":[230],"employed":[232],"optimize":[234],"global":[236],"benefit":[237],"list.":[241],"Extensive":[242],"offline":[243],"experiments":[244],"A/B":[247],"tests":[248],"performed":[250],"in":[251],"real-world":[253],"system":[254],"demonstrate":[256],"effectiveness":[258],"proposed":[261],"framework.":[262]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}