{"id":"https://openalex.org/W4414603263","doi":"https://doi.org/10.1109/access.2025.3615136","title":"Dynamic Advertisement Pricing and Bidding Optimization: An Integrated Machine Learning and Auction Framework","display_name":"Dynamic Advertisement Pricing and Bidding Optimization: An Integrated Machine Learning and Auction Framework","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414603263","doi":"https://doi.org/10.1109/access.2025.3615136"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3615136","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3615136","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3615136","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5110547700","display_name":"N. Shahin Nazeeba Banu","orcid":null},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"N. Najeetha Banu","raw_affiliation_strings":["Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India","institution_ids":["https://openalex.org/I164861460"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119761205","display_name":"Akilesh C. Harti","orcid":null},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Akilesh C. Harti","raw_affiliation_strings":["Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India","institution_ids":["https://openalex.org/I164861460"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119761206","display_name":"Naveeth Meeran","orcid":null},"institutions":[{"id":"https://openalex.org/I1343180700","display_name":"Intel (United States)","ror":"https://ror.org/01ek73717","country_code":"US","type":"company","lineage":["https://openalex.org/I1343180700"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Naveeth Meeran","raw_affiliation_strings":["Intel Corporation, 2111 NE 25th Ave, Hillsboro, OR, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intel Corporation, 2111 NE 25th Ave, Hillsboro, OR, United States","institution_ids":["https://openalex.org/I1343180700"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039138600","display_name":"G Poornalatha","orcid":null},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"G. Poornalatha","raw_affiliation_strings":["Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India"],"raw_orcid":"https://orcid.org/0000-0001-9620-5526","affiliations":[{"raw_affiliation_string":"Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India","institution_ids":["https://openalex.org/I164861460"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040659585","display_name":"K. B. Ajitha Shenoy","orcid":"https://orcid.org/0000-0003-3995-1826"},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"K. B. Ajitha Shenoy","raw_affiliation_strings":["Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India"],"raw_orcid":"https://orcid.org/0000-0003-3995-1826","affiliations":[{"raw_affiliation_string":"Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India","institution_ids":["https://openalex.org/I164861460"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5110547700"],"corresponding_institution_ids":["https://openalex.org/I164861460"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.32834396,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9937000274658203,"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"}},"topics":[{"id":"https://openalex.org/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9937000274658203,"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/T11182","display_name":"Auction Theory and Applications","score":0.9236999750137329,"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/bidding","display_name":"Bidding","score":0.8634999990463257},{"id":"https://openalex.org/keywords/real-time-bidding","display_name":"Real-time bidding","score":0.7014999985694885},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.5461999773979187},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5220000147819519},{"id":"https://openalex.org/keywords/ebidding","display_name":"Ebidding","score":0.46380001306533813},{"id":"https://openalex.org/keywords/online-advertising","display_name":"Online advertising","score":0.46299999952316284},{"id":"https://openalex.org/keywords/display-advertising","display_name":"Display advertising","score":0.45080000162124634},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.40939998626708984}],"concepts":[{"id":"https://openalex.org/C9233905","wikidata":"https://www.wikidata.org/wiki/Q3276328","display_name":"Bidding","level":2,"score":0.8634999990463257},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7411999702453613},{"id":"https://openalex.org/C1525070","wikidata":"https://www.wikidata.org/wiki/Q2134714","display_name":"Real-time bidding","level":3,"score":0.7014999985694885},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5461999773979187},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5220000147819519},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49239999055862427},{"id":"https://openalex.org/C143989560","wikidata":"https://www.wikidata.org/wiki/Q17011617","display_name":"Ebidding","level":3,"score":0.46380001306533813},{"id":"https://openalex.org/C512338625","wikidata":"https://www.wikidata.org/wiki/Q624902","display_name":"Online advertising","level":3,"score":0.46299999952316284},{"id":"https://openalex.org/C2777999536","wikidata":"https://www.wikidata.org/wiki/Q2399498","display_name":"Display advertising","level":4,"score":0.45080000162124634},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43689998984336853},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.40939998626708984},{"id":"https://openalex.org/C115174607","wikidata":"https://www.wikidata.org/wiki/Q1100934","display_name":"Click-through rate","level":2,"score":0.40860000252723694},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.4047999978065491},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4020000100135803},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.3580999970436096},{"id":"https://openalex.org/C74979957","wikidata":"https://www.wikidata.org/wiki/Q4819604","display_name":"Auction algorithm","level":5,"score":0.3296000063419342},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2930000126361847},{"id":"https://openalex.org/C78597825","wikidata":"https://www.wikidata.org/wiki/Q484847","display_name":"E-commerce","level":2,"score":0.28630000352859497},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.28540000319480896},{"id":"https://openalex.org/C2779391423","wikidata":"https://www.wikidata.org/wiki/Q17009728","display_name":"Dynamic pricing","level":2,"score":0.27379998564720154},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.26899999380111694},{"id":"https://openalex.org/C11276805","wikidata":"https://www.wikidata.org/wiki/Q771334","display_name":"Auction theory","level":3,"score":0.2678999900817871},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.2621000111103058},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2614000141620636}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3615136","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3615136","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:583d80f4cf7c42c9821be5a8ed3824a0","is_oa":true,"landing_page_url":"https://doaj.org/article/583d80f4cf7c42c9821be5a8ed3824a0","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 170360-170371 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3615136","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3615136","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Online":[0],"advertising":[1,178],"platforms":[2],"rely":[3],"on":[4],"efficient":[5],"pricing":[6],"and":[7,18,29,42,54,62,72,151,164,173],"bidding":[8,121],"strategies":[9,122],"to":[10,99,107,110,175],"maximize":[11],"returns":[12],"for":[13],"advertisers":[14],"while":[15],"maintaining":[16],"fairness":[17,40],"competitiveness":[19],"in":[20,91,161],"auctions.":[21],"This":[22],"paper":[23],"presents":[24],"an":[25],"integrated":[26],"machine":[27],"learning":[28],"auction-based":[30],"framework":[31,168],"that":[32,119],"combines":[33],"Click-Through":[34],"Rate":[35],"(CTR)":[36],"prediction,":[37],"convex":[38,93],"optimization,":[39],"evaluation,":[41],"multi-agent":[43,114],"auction":[44,116],"simulation.":[45],"Synthetic":[46],"datasets":[47],"mimicking":[48],"real-world":[49],"ad":[50],"environments":[51],"were":[52,64,89],"generated,":[53],"multiple":[55],"models,":[56],"including":[57],"Logistic":[58],"Regression,":[59],"Random":[60],"Forest,":[61],"XGBoost,":[63],"evaluated.":[65],"XGBoost":[66],"achieved":[67],"the":[68,82,155,158],"highest":[69],"ROC-AUC":[70],"(0.8731)":[71],"lowest":[73],"log":[74],"loss":[75],"(0.2187),":[76],"improving":[77],"F1-score":[78],"by":[79,105,126],"12%":[80],"over":[81,128],"baseline":[83],"after":[84],"applying":[85],"SMOTE.":[86],"Predicted":[87],"CTRs":[88],"used":[90],"a":[92,139],"optimization":[94],"model,":[95],"solved":[96],"with":[97],"CVXPY,":[98],"allocate":[100],"budgets":[101],"optimally,":[102],"increasing":[103],"ROI":[104],"up":[106],"23.5%":[108],"compared":[109],"uniform":[111],"bidding.":[112,130],"A":[113],"second-price":[115],"simulation":[117],"demonstrated":[118],"balanced":[120],"improved":[123],"clicks-per-dollar":[124],"efficiency":[125],"22%":[127],"aggressive":[129],"Fairness":[131],"analysis":[132],"across":[133],"gender":[134],"groups":[135],"revealed":[136],"minimal":[137],"disparity,with":[138],"prediction":[140,163],"accuracy":[141],"gap":[142],"of":[143,157],"only":[144],"1.3%.":[145],"Comparative":[146],"evaluation":[147],"against":[148],"LightGBM,":[149],"CatBoost,":[150],"heuristic":[152],"baselines":[153],"confirmed":[154],"superiority":[156],"proposed":[159,167],"method":[160],"both":[162],"ROI.":[165],"The":[166],"is":[169],"computationally":[170],"efficient,":[171],"scalable,":[172],"applicable":[174],"diverse":[176],"online":[177],"scenarios.":[179]},"counts_by_year":[],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}