{"id":"https://openalex.org/W4284713552","doi":"https://doi.org/10.1145/3477495.3531911","title":"Posterior Probability Matters","display_name":"Posterior Probability Matters","publication_year":2022,"publication_date":"2022-07-06","ids":{"openalex":"https://openalex.org/W4284713552","doi":"https://doi.org/10.1145/3477495.3531911"},"language":"en","primary_location":{"id":"doi:10.1145/3477495.3531911","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3477495.3531911","pdf_url":null,"source":{"id":"https://openalex.org/S4363608773","display_name":"Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval","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 45th 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/A5059038918","display_name":"Penghui Wei","orcid":"https://orcid.org/0000-0002-8701-9833"},"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":true,"raw_author_name":"Penghui Wei","raw_affiliation_strings":["Alibaba Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Beijing, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100340717","display_name":"Weimin Zhang","orcid":"https://orcid.org/0000-0001-6632-0144"},"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":"Weimin Zhang","raw_affiliation_strings":["Alibaba Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Beijing, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016465425","display_name":"Ruijie Hou","orcid":"https://orcid.org/0000-0002-0878-9988"},"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":"Ruijie Hou","raw_affiliation_strings":["Alibaba Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Beijing, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040706602","display_name":"Jinquan Liu","orcid":"https://orcid.org/0000-0003-2326-0684"},"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":"Jinquan Liu","raw_affiliation_strings":["Alibaba Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Beijing, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077857118","display_name":"Shaoguo Liu","orcid":"https://orcid.org/0000-0002-3058-5383"},"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":"Shaoguo Liu","raw_affiliation_strings":["Alibaba Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Beijing, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100456467","display_name":"Liang Wang","orcid":"https://orcid.org/0000-0001-5339-7484"},"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":"Liang Wang","raw_affiliation_strings":["Alibaba Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Beijing, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073856221","display_name":"Bo Zheng","orcid":"https://orcid.org/0000-0002-4037-6315"},"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":"Bo Zheng","raw_affiliation_strings":["Alibaba Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Beijing, China","institution_ids":["https://openalex.org/I45928872"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5059038918"],"corresponding_institution_ids":["https://openalex.org/I45928872"],"apc_list":null,"apc_paid":null,"fwci":1.1675,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.80946255,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2645","last_page":"2649"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9994000196456909,"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":0.9994000196456909,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.9945999979972839,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.7591198682785034},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7180720567703247},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.7061593532562256},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5564793348312378},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5504553914070129},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5290117859840393},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40579432249069214},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3944196105003357},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37323713302612305},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.25684237480163574},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2513916790485382},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17859241366386414}],"concepts":[{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.7591198682785034},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7180720567703247},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.7061593532562256},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5564793348312378},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5504553914070129},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5290117859840393},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40579432249069214},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3944196105003357},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37323713302612305},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.25684237480163574},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2513916790485382},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17859241366386414},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3477495.3531911","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3477495.3531911","pdf_url":null,"source":{"id":"https://openalex.org/S4363608773","display_name":"Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval","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 45th International ACM SIGIR Conference on Research and Development in Information Retrieval","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":16,"referenced_works":["https://openalex.org/W2012942264","https://openalex.org/W2074694452","https://openalex.org/W2076618162","https://openalex.org/W2475334473","https://openalex.org/W2512971201","https://openalex.org/W2723293840","https://openalex.org/W2896921640","https://openalex.org/W2962989965","https://openalex.org/W3001835520","https://openalex.org/W3102243698","https://openalex.org/W3210101630","https://openalex.org/W4200631330","https://openalex.org/W4212774754","https://openalex.org/W4221154425","https://openalex.org/W4224325518","https://openalex.org/W4297971002"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4290792893","https://openalex.org/W4306674287","https://openalex.org/W4224009465","https://openalex.org/W4286629047","https://openalex.org/W4306321456","https://openalex.org/W4285260836","https://openalex.org/W3046775127","https://openalex.org/W3170094116","https://openalex.org/W4323349240"],"abstract_inverted_index":{"Predicting":[0],"user":[1],"response":[2],"probabilities":[3],"is":[4,48,88],"vital":[5],"for":[6,90],"ad":[7],"ranking":[8],"and":[9,50,78,112],"bidding.":[10],"We":[11],"hope":[12],"that":[13,21,85,99],"predictive":[14],"models":[15],"can":[16],"produce":[17],"accurate":[18],"probabilistic":[19],"predictions":[20,31,71],"reflect":[22],"true":[23],"likelihoods.":[24],"Calibration":[25],"techniques":[26],"aims":[27],"to":[28,32,42,68,83,94],"post-process":[29],"model":[30,70],"posterior":[33,76,87],"probabilities.":[34],"Field-level":[35],"calibration":[36,40,105],"--":[37,47],"which":[38],"performs":[39],"w.r.t.":[41],"a":[43,58],"specific":[44],"field":[45,92],"value":[46,93],"fine-grained":[49],"more":[51],"practical.":[52],"In":[53],"this":[54],"paper":[55],"we":[56],"propose":[57],"doubly-adaptive":[59],"approach":[60],"AdaCalib.":[61],"It":[62,107],"learns":[63],"an":[64],"isotonic":[65],"function":[66],"family":[67],"calibrate":[69],"with":[72],"the":[73,86,91],"guidance":[74],"of":[75],"statistics,":[77],"field-adaptive":[79],"mechanisms":[80],"are":[81],"designed":[82],"ensure":[84],"appropriate":[89],"be":[95],"calibrated.":[96],"Experiments":[97],"verify":[98],"AdaCalib":[100],"achieves":[101],"significant":[102],"improvement":[103],"on":[104],"performance.":[106],"has":[108],"been":[109],"deployed":[110],"online":[111],"beats":[113],"previous":[114],"approach.":[115]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
