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Applying Machine Learning in Marketing: An Analysis Using the NMF and k-Means Algorithms

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Applying Machine Learning in Marketing: An Analysis Using the NMF and k-Means Algorithms

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dc.contributor.author Gallego Hidalgo, Víctor es_ES
dc.contributor.author Lingan, Jessica es_ES
dc.contributor.author Freixes, Alfons es_ES
dc.contributor.author Juan, Angel A. es_ES
dc.contributor.author Osorio-Muñoz, Celia es_ES
dc.date.accessioned 2024-10-07T18:07:43Z
dc.date.available 2024-10-07T18:07:43Z
dc.date.issued 2024-07 es_ES
dc.identifier.uri http://hdl.handle.net/10251/209464
dc.description.abstract [EN] The integration of machine learning (ML) techniques into marketing strategies has become increasingly relevant in modern business. Utilizing scientific manuscripts indexed in the Scopus database, this article explores how this integration is being carried out. Initially, a focused search is undertaken for academic articles containing both the terms "machine learning" and "marketing" in their titles, which yields a pool of papers. These papers have been processed using the Supabase platform. The process has included steps like text refinement and feature extraction. In addition, our study uses two key ML methodologies: topic modeling through NMF and a comparative analysis utilizing the k-means clustering algorithm. Through this analysis, three distinct clusters emerged, thus clarifying how ML techniques are influencing marketing strategies, from enhancing customer segmentation practices to optimizing the effectiveness of advertising campaigns. es_ES
dc.description.sponsorship This work was founded by the Investigo Program of the Generalitat Valenciana (INVEST/2023/304), Coca-Cola Europacific Partners, and the Spanish Ministry of Science and Innovation (PID2022-138860NB-I00 and RED2022-134703-T). es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Information es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Machine learning es_ES
dc.subject Digital marketing es_ES
dc.subject Algorithms es_ES
dc.subject Artificial intelligence es_ES
dc.subject.classification ESTADISTICA E INVESTIGACION OPERATIVA es_ES
dc.title Applying Machine Learning in Marketing: An Analysis Using the NMF and k-Means Algorithms es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/info15070368 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2022-138860NB-I00/ES/INTELIGENCIA ARTIFICIAL E INTERNET DE LAS COSAS PARA OPTIMIZAR EL CONSUMO ENERGETICO EN EL TRANSPORTE CON VEHICULOS ELECTRICOS/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//INVEST%2F2023%2F304/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//RED2022-134703-T/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Politécnica Superior de Alcoy - Escola Politècnica Superior d'Alcoi es_ES
dc.description.bibliographicCitation Gallego Hidalgo, V.; Lingan, J.; Freixes, A.; Juan, AA.; Osorio-Muñoz, C. (2024). Applying Machine Learning in Marketing: An Analysis Using the NMF and k-Means Algorithms. Information. 15(7). https://doi.org/10.3390/info15070368 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/info15070368 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 15 es_ES
dc.description.issue 7 es_ES
dc.identifier.eissn 2078-2489 es_ES
dc.relation.pasarela S\525275 es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.contributor.funder Ministerio de Ciencia e Innovación es_ES


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