{"id":"https://openalex.org/W2033798573","doi":"https://doi.org/10.1145/2020408.2020604","title":"Real-time bidding algorithms for performance-based display ad allocation","display_name":"Real-time bidding algorithms for performance-based display ad allocation","publication_year":2011,"publication_date":"2011-08-21","ids":{"openalex":"https://openalex.org/W2033798573","doi":"https://doi.org/10.1145/2020408.2020604","mag":"2033798573"},"language":"en","primary_location":{"id":"doi:10.1145/2020408.2020604","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2020408.2020604","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining","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/A5100359116","display_name":"Ye Chen","orcid":"https://orcid.org/0000-0002-9044-745X"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ye Chen","raw_affiliation_strings":["Microsoft, Redmond, CA, USA","Microsoft, Redmond, CA, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft, Redmond, CA, USA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"Microsoft, Redmond, CA, USA#TAB#","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016845215","display_name":"Pavel Berkhin","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pavel Berkhin","raw_affiliation_strings":["Microsoft, Redmond, CA, USA","Microsoft, Redmond, CA, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft, Redmond, CA, USA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"Microsoft, Redmond, CA, USA#TAB#","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103480492","display_name":"Bo Anderson","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bo Anderson","raw_affiliation_strings":["Microsoft, Redmond, CA, USA","Microsoft, Redmond, CA, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft, Redmond, CA, USA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"Microsoft, Redmond, CA, USA#TAB#","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060217026","display_name":"Nikhil R. Devanur","orcid":"https://orcid.org/0009-0005-4406-5935"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nikhil R. Devanur","raw_affiliation_strings":["Microsoft Research, Redmond, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research, Redmond, CA, USA","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":10.1601,"has_fulltext":false,"cited_by_count":126,"citation_normalized_percentile":{"value":0.98210923,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1307","last_page":"1315"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11182","display_name":"Auction Theory and Applications","score":0.9998999834060669,"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/T11182","display_name":"Auction Theory and Applications","score":0.9998999834060669,"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/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9994000196456909,"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/T10328","display_name":"Supply Chain and Inventory Management","score":0.9927999973297119,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7650481462478638},{"id":"https://openalex.org/keywords/bidding","display_name":"Bidding","score":0.7450709939002991},{"id":"https://openalex.org/keywords/real-time-bidding","display_name":"Real-time bidding","score":0.5966395139694214},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5607565641403198},{"id":"https://openalex.org/keywords/display-advertising","display_name":"Display advertising","score":0.5424990057945251},{"id":"https://openalex.org/keywords/budget-constraint","display_name":"Budget constraint","score":0.459803968667984},{"id":"https://openalex.org/keywords/valuation","display_name":"Valuation (finance)","score":0.4481757879257202},{"id":"https://openalex.org/keywords/linear-programming","display_name":"Linear programming","score":0.41220617294311523},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.41126903891563416},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.28737589716911316},{"id":"https://openalex.org/keywords/online-advertising","display_name":"Online advertising","score":0.25480765104293823},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10378363728523254}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7650481462478638},{"id":"https://openalex.org/C9233905","wikidata":"https://www.wikidata.org/wiki/Q3276328","display_name":"Bidding","level":2,"score":0.7450709939002991},{"id":"https://openalex.org/C1525070","wikidata":"https://www.wikidata.org/wiki/Q2134714","display_name":"Real-time bidding","level":3,"score":0.5966395139694214},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5607565641403198},{"id":"https://openalex.org/C2777999536","wikidata":"https://www.wikidata.org/wiki/Q2399498","display_name":"Display advertising","level":4,"score":0.5424990057945251},{"id":"https://openalex.org/C8505890","wikidata":"https://www.wikidata.org/wiki/Q605095","display_name":"Budget constraint","level":2,"score":0.459803968667984},{"id":"https://openalex.org/C186027771","wikidata":"https://www.wikidata.org/wiki/Q4008379","display_name":"Valuation (finance)","level":2,"score":0.4481757879257202},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.41220617294311523},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.41126903891563416},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28737589716911316},{"id":"https://openalex.org/C512338625","wikidata":"https://www.wikidata.org/wiki/Q624902","display_name":"Online advertising","level":3,"score":0.25480765104293823},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10378363728523254},{"id":"https://openalex.org/C133425853","wikidata":"https://www.wikidata.org/wiki/Q60571","display_name":"Neoclassical economics","level":1,"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/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"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/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2020408.2020604","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2020408.2020604","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.232.1080","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.232.1080","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://research.microsoft.com/en-us/um/people/nikdev/pubs/rtb-perf.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1484554259","https://openalex.org/W1513595680","https://openalex.org/W1541708866","https://openalex.org/W1554763265","https://openalex.org/W1763790326","https://openalex.org/W1969675113","https://openalex.org/W2029050771","https://openalex.org/W2060204748","https://openalex.org/W2113098938","https://openalex.org/W2118962121","https://openalex.org/W2158635658","https://openalex.org/W2162979096","https://openalex.org/W2341361985","https://openalex.org/W2560674852","https://openalex.org/W2916858558","https://openalex.org/W3121172388","https://openalex.org/W4241226388","https://openalex.org/W6630807028"],"related_works":["https://openalex.org/W2532780566","https://openalex.org/W3099082736","https://openalex.org/W4385421505","https://openalex.org/W341704063","https://openalex.org/W4385565986","https://openalex.org/W3166393923","https://openalex.org/W3099947523","https://openalex.org/W3004257040","https://openalex.org/W4306317496","https://openalex.org/W3006297623"],"abstract_inverted_index":{"We":[0],"describe":[1],"a":[2,29,57,84,105,139],"real-time":[3,106,118,127,147,199,216],"bidding":[4,107,148,235],"algorithm":[5,108,149,176],"for":[6],"performance-based":[7],"display":[8,16],"ad":[9,22,95,244],"allocation.":[10],"A":[11],"central":[12],"issue":[13],"in":[14],"performance":[15],"advertising":[17],"is":[18,49,150],"matching":[19],"campaigns":[20],"to":[21,37,50,68,87,92,94,126,155,165,203,205],"impressions,":[23],"which":[24],"can":[25],"be":[26],"formulated":[27],"as":[28,40,169],"constrained":[30],"optimization":[31,53,189],"problem":[32,54,159,168],"that":[33,109,137,247],"maximizes":[34],"revenue":[35],"subject":[36],"constraints":[38],"such":[39],"budget":[41,131],"limits":[42],"and":[43,67,121,195,223],"inventory":[44],"availability.":[45],"The":[46],"current":[47],"practice":[48],"solve":[51],"the":[52,64,74,98,145,156,162,166,174,178,182,206,210,224,231],"offline":[55,81,179,188],"at":[56,97],"tractable":[58],"level":[59,184],"of":[60,185,209],"impression":[61,100,112],"granularity":[62],"(e.g.,":[63,114,130],"page":[65],"level),":[66],"serve":[69],"ads":[70],"online":[71,153,175],"based":[72,229],"on":[73,230],"precomputed":[75],"static":[76],"delivery":[77,245],"scheme.":[78],"Although":[79],"this":[80],"approach":[82],"takes":[83],"global":[85],"view":[86],"achieve":[88],"optimality,":[89],"it":[90],"fails":[91],"scale":[93],"allocation":[96],"individual":[99],"level.":[101],"Therefore,":[102],"we":[103,135,193,238],"propose":[104],"enables":[110],"fine-grained":[111],"valuation":[113],"targeting":[115],"users":[116],"with":[117,197,242],"conversion":[119],"data),":[120],"adjusts":[122,213,226],"value-based":[123],"bids":[124,214,227],"according":[125],"constraint":[128,217],"snapshots":[129],"consumption":[132],"levels).":[133],"Theoretically,":[134],"show":[136,239],"under":[138],"linear":[140],"programming":[141],"(LP)":[142],"primal-dual":[143],"formulation,":[144],"simple":[146],"indeed":[151],"an":[152,187],"solver":[154],"original":[157],"primal":[158],"by":[160],"taking":[161],"optimal":[163],"solution":[164],"dual":[167],"input.":[170],"In":[171],"other":[172,225],"words,":[173],"guarantees":[177],"optimality":[180],"given":[181],"same":[183],"knowledge":[186],"would":[190],"have.":[191],"Empirically,":[192],"develop":[194],"experiment":[196],"two":[198],"bid":[200],"adjustment":[201],"approaches":[202],"adapting":[204],"non-stationary":[207],"nature":[208],"marketplace:":[211],"one":[212],"against":[215],"satisfaction":[218],"levels":[219],"using":[220],"control-theoretic":[221],"methods,":[222],"also":[228],"statistically":[232],"modeled":[233],"historical":[234],"landscape.":[236],"Finally,":[237],"experimental":[240],"results":[241],"real-world":[243],"data":[246],"support":[248],"our":[249],"theoretical":[250],"conclusions.":[251]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":21},{"year":2016,"cited_by_count":13},{"year":2015,"cited_by_count":12},{"year":2014,"cited_by_count":11},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":10}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}