{"id":"https://openalex.org/W2999324038","doi":"https://doi.org/10.1007/s41019-019-00115-y","title":"Deep Learning for User Interest and Response Prediction in Online Display Advertising","display_name":"Deep Learning for User Interest and Response Prediction in Online Display Advertising","publication_year":2020,"publication_date":"2020-01-17","ids":{"openalex":"https://openalex.org/W2999324038","doi":"https://doi.org/10.1007/s41019-019-00115-y","mag":"2999324038"},"language":"en","primary_location":{"id":"doi:10.1007/s41019-019-00115-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41019-019-00115-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41019-019-00115-y.pdf","source":{"id":"https://openalex.org/S2486411021","display_name":"Data Science and Engineering","issn_l":"2364-1185","issn":["2364-1185","2364-1541"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Science and Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://link.springer.com/content/pdf/10.1007/s41019-019-00115-y.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000240922","display_name":"Zhabiz Gharibshah","orcid":null},"institutions":[{"id":"https://openalex.org/I63772739","display_name":"Florida Atlantic University","ror":"https://ror.org/05p8w6387","country_code":"US","type":"education","lineage":["https://openalex.org/I63772739"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhabiz Gharibshah","raw_affiliation_strings":["Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, 33431, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, 33431, USA","institution_ids":["https://openalex.org/I63772739"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084641325","display_name":"Xingquan Zhu","orcid":"https://orcid.org/0000-0003-4129-9611"},"institutions":[{"id":"https://openalex.org/I63772739","display_name":"Florida Atlantic University","ror":"https://ror.org/05p8w6387","country_code":"US","type":"education","lineage":["https://openalex.org/I63772739"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xingquan Zhu","raw_affiliation_strings":["Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, 33431, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, 33431, USA","institution_ids":["https://openalex.org/I63772739"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004236976","display_name":"Arthur Hainline","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Arthur Hainline","raw_affiliation_strings":["Bidtellect Inc., Delray Beach, FL, 33483, USA"],"affiliations":[{"raw_affiliation_string":"Bidtellect Inc., Delray Beach, FL, 33483, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024836029","display_name":"Michael Conway","orcid":"https://orcid.org/0000-0002-0848-8835"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Michael Conway","raw_affiliation_strings":["Bidtellect Inc., Delray Beach, FL, 33483, USA"],"affiliations":[{"raw_affiliation_string":"Bidtellect Inc., Delray Beach, FL, 33483, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5000240922"],"corresponding_institution_ids":["https://openalex.org/I63772739"],"apc_list":null,"apc_paid":null,"fwci":23.0898,"has_fulltext":true,"cited_by_count":113,"citation_normalized_percentile":{"value":0.99455052,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"5","issue":"1","first_page":"12","last_page":"26"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9995999932289124,"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":0.9995999932289124,"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/T10609","display_name":"Digital Marketing and Social Media","score":0.9926000237464905,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8003321290016174},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6354414224624634},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6009995341300964},{"id":"https://openalex.org/keywords/click-through-rate","display_name":"Click-through rate","score":0.5804544687271118},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46120068430900574},{"id":"https://openalex.org/keywords/display-advertising","display_name":"Display advertising","score":0.4520133435726166},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4476163983345032},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.44727805256843567},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4461720883846283},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43782538175582886},{"id":"https://openalex.org/keywords/online-advertising","display_name":"Online advertising","score":0.39854931831359863},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.2322370409965515},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.19855251908302307},{"id":"https://openalex.org/keywords/the-internet","display_name":"The Internet","score":0.17357420921325684}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8003321290016174},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6354414224624634},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6009995341300964},{"id":"https://openalex.org/C115174607","wikidata":"https://www.wikidata.org/wiki/Q1100934","display_name":"Click-through rate","level":2,"score":0.5804544687271118},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46120068430900574},{"id":"https://openalex.org/C2777999536","wikidata":"https://www.wikidata.org/wiki/Q2399498","display_name":"Display advertising","level":4,"score":0.4520133435726166},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4476163983345032},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.44727805256843567},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4461720883846283},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43782538175582886},{"id":"https://openalex.org/C512338625","wikidata":"https://www.wikidata.org/wiki/Q624902","display_name":"Online advertising","level":3,"score":0.39854931831359863},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2322370409965515},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.19855251908302307},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.17357420921325684},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s41019-019-00115-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41019-019-00115-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41019-019-00115-y.pdf","source":{"id":"https://openalex.org/S2486411021","display_name":"Data Science and Engineering","issn_l":"2364-1185","issn":["2364-1185","2364-1541"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Science and Engineering","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:f557f2697b764a788b801f195711d7b8","is_oa":true,"landing_page_url":"https://doaj.org/article/f557f2697b764a788b801f195711d7b8","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Data Science and Engineering, Vol 5, Iss 1, Pp 12-26 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s41019-019-00115-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41019-019-00115-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41019-019-00115-y.pdf","source":{"id":"https://openalex.org/S2486411021","display_name":"Data Science and Engineering","issn_l":"2364-1185","issn":["2364-1185","2364-1541"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Science and Engineering","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3849742459","display_name":null,"funder_award_id":"1828181","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G942469231","display_name":null,"funder_award_id":"CNS-1828181","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2999324038.pdf","grobid_xml":"https://content.openalex.org/works/W2999324038.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1598796236","https://openalex.org/W1832693441","https://openalex.org/W1893290116","https://openalex.org/W1969675113","https://openalex.org/W1976517433","https://openalex.org/W1983548143","https://openalex.org/W1985759455","https://openalex.org/W2043840617","https://openalex.org/W2090883204","https://openalex.org/W2132504805","https://openalex.org/W2186584675","https://openalex.org/W2274884803","https://openalex.org/W2295739661","https://openalex.org/W2539781657","https://openalex.org/W2548570154","https://openalex.org/W2568885412","https://openalex.org/W2569307494","https://openalex.org/W2604662567","https://openalex.org/W2615162663","https://openalex.org/W2622692433","https://openalex.org/W2769616392","https://openalex.org/W2783175414","https://openalex.org/W2799154700","https://openalex.org/W2949274928","https://openalex.org/W2951241690","https://openalex.org/W2962745591","https://openalex.org/W2964132437","https://openalex.org/W2964236337","https://openalex.org/W2966095869","https://openalex.org/W3096591391"],"related_works":["https://openalex.org/W2100597815","https://openalex.org/W175164097","https://openalex.org/W2143648166","https://openalex.org/W2952316437","https://openalex.org/W4300589523","https://openalex.org/W2591602503","https://openalex.org/W2162862818","https://openalex.org/W3120879483","https://openalex.org/W2078847107","https://openalex.org/W2096414357"],"abstract_inverted_index":{"Abstract":[0],"User":[1],"interest":[2,125],"and":[3,24,72,87,92,113,123,143,173,191,206,220],"behavior":[4],"modeling":[5],"is":[6,129],"a":[7,48,68,137,148,151,170],"critical":[8],"step":[9],"in":[10,89,213,215],"online":[11],"digital":[12],"advertising.":[13],"On":[14,31],"the":[15,27,32,41,134,145,159,167],"one":[16],"hand,":[17,34],"user":[18,35,90,120,124,138,149,185,210,216,223],"interests":[19,36,186],"directly":[20],"impact":[21],"their":[22],"response":[23,218],"actions":[25],"to":[26,77,130,166,180,199],"displayed":[28,165],"advertisement":[29],"(Ad).":[30],"other":[33],"can":[37],"further":[38],"help":[39],"determine":[40],"probability":[42,135,146],"of":[43,136,147,154,209],"an":[44,141],"Ad":[45,56,142,155,217,224],"viewer":[46],"becoming":[47],"buying":[49],"customer.":[50],"To":[51,157],"date,":[52],"existing":[53,200],"methods":[54],"for":[55,98,119],"click":[57,121,225],"prediction,":[58,62],"or":[59],"click-through":[60],"rate":[61],"mainly":[63],"consider":[64,84],"representing":[65],"users":[66,168],"as":[67,169,187],"static":[69,201],"feature":[70],"set":[71],"train":[73],"machine":[74],"learning":[75],"classifiers":[76],"predict":[78,132],"clicks.":[79],"Such":[80],"approaches":[81],"do":[82],"not":[83],"temporal":[85,171,207],"variance":[86,208],"changes":[88],"behaviors,":[91],"solely":[93],"rely":[94],"on":[95,140,193],"given":[96],"features":[97,182],"learning.":[99],"In":[100],"this":[101],"paper,":[102],"we":[103,161],"propose":[104],"two":[105],"deep":[106],"learning-based":[107],"frameworks,":[108],"$${\\hbox":[109,114],"{LSTM}}_{\\mathrm{cp}}$$":[110],"<mml:math":[111,116],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"><mml:msub><mml:mtext>LSTM</mml:mtext><mml:mi>cp</mml:mi></mml:msub></mml:math>":[112],"{LSTM}}_{\\mathrm{ip}}$$":[115],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"><mml:msub><mml:mtext>LSTM</mml:mtext><mml:mi>ip</mml:mi></mml:msub></mml:math>":[117],",":[118],"prediction":[122,219],"modeling.":[126],"Our":[127],"goal":[128],"accurately":[131],"(1)":[133],"clicking":[139,150],"(2)":[144],"specific":[152,222],"type":[153],"campaign.":[156],"achieve":[158],"goal,":[160],"collect":[162],"page":[163],"information":[164],"sequence":[172],"use":[174],"long":[175],"short-term":[176],"memory":[177],"(LSTM)":[178],"network":[179],"learn":[181],"that":[183],"represents":[184],"latent":[188],"features.":[189],"Experiments":[190],"comparisons":[192],"real-world":[194],"data":[195],"show":[196],"that,":[197],"compared":[198],"set-based":[202],"approaches,":[203],"considering":[204],"sequences":[205],"requests":[211],"results":[212],"improvements":[214],"campaign":[221],"prediction.":[226]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":18},{"year":2021,"cited_by_count":33},{"year":2020,"cited_by_count":15}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}