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dc.contributor.authorPonce, Hiram
dc.contributor.authorMartinez-Villaseñor, Lourdes
dc.coverage.spatialMéxico
dc.creatorMARÍA DE LOURDES GUADALUPE MARTÍNEZ VILLASEÑOR;241561
dc.date.accessioned2018-02-23T17:18:51Z
dc.date.available2018-02-23T17:18:51Z
dc.date.issued2017
dc.identifier.citationMiralles-Pechuán, L., Ponce, H., Martínez-Villaseñor, L. (2017). A novel methodology for optimizing display advertising campaigns using genetic algorithms. Electronic Commerce Research and Applications, 27, 39-51.es_ES, en_US
dc.identifier.issn1567-4223
dc.identifier.otherCampus Ciudad de México
dc.identifier.urihttps://hdl.handle.net/20.500.12552/4471
dc.identifier.urihttp://dx.doi.org/10.1016/j.elerap.2017.11.004
dc.description.abstractOnline advertising campaigns have attracted the attention of many advertisers willing to promote their business on the Internet. One of the main problems faced by advertisers, especially by those who have little experience in Internet advertising, is configuring their campaigns in an efficient way. To configure a campaign properly it is required to select the appropriate target, so it is guaranteed a high acceptance of users to adverts. It is also required that the number of visits that satisfy the configuration requirements is high enough to cover the advertisers’ campaigns. Thus, this paper presents a novel methodology for optimizing the micro-targeting technique in direct response display advertising campaigns by using genetic algorithms as the basis optimization model and a machine-learning based click-through rate (CTR) model. We implement our methodology to optimize display advertising campaigns on mobile devices using a real dataset. Results show that our methodology is feasible to optimize the campaigns by selecting the set of the best features required. Also, customization of the advertising campaign selecting some features by an advertiser, e.g. applying micro-targeting, can be optimized efficiently. © 2017 Elsevier B.V.es_ES, en_US
dc.description.statementofresponsibilityInvestigadores
dc.description.statementofresponsibilityEstudiantes
dc.description.statementofresponsibilityMaestros
dc.description.tableofcontentsIngeniería
dc.language.isoespes_ES, en_US
dc.publisherElsevier B.V.
dc.relationVersión aceptada
dc.rightsAcceso Embargado
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.urihttp://www.sherpa.ac.uk/romeo/issn/1567-4223/
dc.sourceElectronic Commerce Research and Applications
dc.subjectDisplay devicesen
dc.subjectLearning algorithmsen
dc.subjectLearning systemsen
dc.subjectAdvertising campaignen
dc.subjectClick-through rateen
dc.subjectDirect responseen
dc.subjectDisplay advertisingsen
dc.subjectInternet advertisingen
dc.subjectOnline advertisingen
dc.subjectOptimization modelingen
dc.subjectMarketingen
dc.subjectDirect responseen
dc.subjectOptimizationen
dc.subjectDisplay advertising campaignsen
dc.subjectGenetic algorithmsen
dc.subjectMachine learningen
dc.subjectMicro-targetingen
dc.subject.classificationINGENIERÍA Y TECNOLOGÍA
dc.titleA novel methodology for optimizing display advertising campaigns using genetic algorithmses_ES, en_US
dc.typeArtícluloes_ES, en_US


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