{"id":"https://openalex.org/W2138236359","doi":"https://doi.org/10.1109/icdmw.2010.157","title":"Large-Scale Customized Models for Advertisers","display_name":"Large-Scale Customized Models for Advertisers","publication_year":2010,"publication_date":"2010-12-01","ids":{"openalex":"https://openalex.org/W2138236359","doi":"https://doi.org/10.1109/icdmw.2010.157","mag":"2138236359"},"language":"en","primary_location":{"id":"doi:10.1109/icdmw.2010.157","doi":"https://doi.org/10.1109/icdmw.2010.157","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdmw.2010.157","pdf_url":null,"source":{"id":"https://openalex.org/S4393918563","display_name":"IEEE ... International Conference on Data Mining workshops","issn_l":"2375-9259","issn":["2375-9259"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["norway-1"],"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":"2010 IEEE International Conference on Data Mining Workshops","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5025092213","display_name":"Abraham Bagherjeiran","orcid":"https://orcid.org/0000-0001-5901-3269","observed_orcids":["https://orcid.org/0000-0001-5901-3269"]},"institutions":[{"id":"https://openalex.org/I4210134091","display_name":"Yahoo (United States)","ror":"https://ror.org/040dkzz12","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134091"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abraham Bagherjeiran","raw_affiliation_strings":["Yahoo Research Laboratories, Santa Clara, CA, USA","Yahoo! Labs., Santa Clara, CA, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yahoo Research Laboratories, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I4210134091"]},{"raw_affiliation_string":"Yahoo! Labs., Santa Clara, CA, USA#TAB#","institution_ids":["https://openalex.org/I4210134091"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050339058","display_name":"Andrew O. Hatch","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210134091","display_name":"Yahoo (United States)","ror":"https://ror.org/040dkzz12","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134091"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrew Hatch","raw_affiliation_strings":["Yahoo Research Laboratories, Santa Clara, CA, USA","Yahoo! Labs., Santa Clara, CA, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yahoo Research Laboratories, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I4210134091"]},{"raw_affiliation_string":"Yahoo! Labs., Santa Clara, CA, USA#TAB#","institution_ids":["https://openalex.org/I4210134091"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057069732","display_name":"Adwait Ratnaparkhi","orcid":"https://orcid.org/0009-0008-5535-016X","observed_orcids":["https://orcid.org/0009-0008-5535-016X"]},"institutions":[{"id":"https://openalex.org/I4210134091","display_name":"Yahoo (United States)","ror":"https://ror.org/040dkzz12","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134091"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Adwait Ratnaparkhi","raw_affiliation_strings":["Yahoo Research Laboratories, Santa Clara, CA, USA","Yahoo! Labs., Santa Clara, CA, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yahoo Research Laboratories, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I4210134091"]},{"raw_affiliation_string":"Yahoo! Labs., Santa Clara, CA, USA#TAB#","institution_ids":["https://openalex.org/I4210134091"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109211424","display_name":"Rajesh Parekh","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210134091","display_name":"Yahoo (United States)","ror":"https://ror.org/040dkzz12","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134091"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rajesh Parekh","raw_affiliation_strings":["Yahoo Research Laboratories, Santa Clara, CA, USA","Yahoo! Labs., Santa Clara, CA, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yahoo Research Laboratories, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I4210134091"]},{"raw_affiliation_string":"Yahoo! Labs., Santa Clara, CA, USA#TAB#","institution_ids":["https://openalex.org/I4210134091"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210134091"],"apc_list":null,"apc_paid":null,"fwci":1.7788,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.85973181,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":87,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1029","last_page":"1036"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.21389999985694885,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.21389999985694885,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.21150000393390656,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.10840000212192535,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/online-advertising","display_name":"online advertising","score":0.7620000243186951},{"id":"https://openalex.org/keywords/ensemble-classifiers","display_name":"ensemble classifiers","score":0.44699999690055847},{"id":"https://openalex.org/keywords/incremental-learning","display_name":"incremental learning","score":0.43299999833106995},{"id":"https://openalex.org/keywords/audience-targeting","display_name":"audience targeting","score":0.4350000023841858},{"id":"https://openalex.org/keywords/conversion-prediction","display_name":"conversion prediction","score":0.7630000114440918},{"id":"https://openalex.org/keywords/beaconing","display_name":"beaconing","score":0.44200000166893005},{"id":"https://openalex.org/keywords/audience-segmentation","display_name":"audience segmentation","score":0.35899999737739563},{"id":"https://openalex.org/keywords/return-on-advertising-spend","display_name":"return on advertising spend","score":0.5139999985694885}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6246578693389893},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5968317985534668},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3602147102355957},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09104642271995544},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.05941593647003174}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icdmw.2010.157","doi":"https://doi.org/10.1109/icdmw.2010.157","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdmw.2010.157","pdf_url":null,"source":{"id":"https://openalex.org/S4393918563","display_name":"IEEE ... International Conference on Data Mining workshops","issn_l":"2375-9259","issn":["2375-9259"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["norway-1"],"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":"2010 IEEE International Conference on Data Mining Workshops","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1563375353","https://openalex.org/W1577835477","https://openalex.org/W2009727399","https://openalex.org/W2029171417","https://openalex.org/W2060204748","https://openalex.org/W2106728444","https://openalex.org/W2115629999","https://openalex.org/W2118756998","https://openalex.org/W2128186735","https://openalex.org/W2134473739","https://openalex.org/W2156909104","https://openalex.org/W2158052187","https://openalex.org/W2168020168","https://openalex.org/W2170708028","https://openalex.org/W3122458291","https://openalex.org/W4230674625","https://openalex.org/W4235130247"],"related_works":["https://openalex.org/W2559898455","https://openalex.org/W1993971593","https://openalex.org/W2746606756","https://openalex.org/W3211831754","https://openalex.org/W2295023311","https://openalex.org/W1970009355","https://openalex.org/W4213365329","https://openalex.org/W2061380513","https://openalex.org/W2808970140","https://openalex.org/W3007563452"],"abstract_inverted_index":{"Performance":[0],"advertisers":[1,198],"want":[2,99],"to":[3,22,27,51,59,89,100,190],"maximize":[4],"the":[5,12,19,62,81,112,131,166,177,184,192],"return":[6],"on":[7,116,149],"their":[8,94,102],"advertising":[9,14,104,193,203],"spend.":[10],"In":[11],"online":[13,202],"world,":[15],"this":[16,128],"means":[17],"showing":[18],"ad":[20,36,142],"only":[21],"those":[23],"users":[24],"most":[25],"likely":[26,58],"convert":[28],"i.e.":[29],"buy":[30],"a":[31,157,200],"product":[32],"or":[33,155],"service.":[34],"Existing":[35],"targeting":[37,42,46,70],"solutions":[38],"such":[39,67],"as":[40,68,147],"context":[41,132],"and":[43,114,168],"rule-based":[44],"segment":[45],"primarily":[47],"leverage":[48],"marketing":[49],"intuition":[50],"identify":[52,71],"audience":[53,72],"segments":[54,73],"that":[55,109],"would":[56],"be":[57,145],"convert.":[60],"Even":[61],"more":[63],"sophisticated":[64],"model-based":[65],"approaches":[66],"behavioral":[69],"interested":[74],"in":[75,176],"certain":[76],"coarse-grained":[77],"categories":[78],"defined":[79],"by":[80,121],"publisher.":[82],"Advertisers":[83,98],"are":[84,188],"now":[85],"able,":[86],"through":[87],"beaconing,":[88],"tell":[90],"us":[91],"exactly":[92],"who":[93],"preferred":[95],"customers":[96],"are.":[97],"augment":[101,191],"existing":[103,141,173],"campaign":[105,113,143],"with":[106,124,171],"custom":[107,137],"models":[108,138],"learn":[110,180],"from":[111],"focus":[115],"attracting":[117],"new":[118,161],"users.":[119],"Motivated":[120],"our":[122],"experience":[123],"advertisers,":[125],"we":[126,187],"pose":[127],"problem":[129],"within":[130],"of":[133,195],"ensemble":[134,151,167],"learning.":[135],"Building":[136],"for":[139],"an":[140,150],"can":[144],"viewed":[146],"operations":[148],"classifier:":[152],"add,":[153],"modify,":[154],"complement":[156],"classifier.":[158],"An":[159],"ideal":[160],"classifier":[162],"should":[163,179],"incrementally":[164],"improve":[165],"minimize":[169],"overlap":[170],"any":[172],"classifiers":[174],"already":[175],"ensemble-it":[178],"something":[181],"new.":[182],"With":[183],"proposed":[185],"approach":[186],"able":[189],"campaigns":[194],"several":[196],"large":[197,201],"at":[199],"company.":[204]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":5}],"updated_date":"2026-11-06T12:05:46.655746","created_date":"2016-06-24T00:00:00"}