Victor Gallego
Research Subjects
Research Interests
Victor Gallego has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Alfons Freixes
Unit of Business Analytics, EUNCET Business School, 08225 Terrassa, Spain
2 shared publications - Jessica Lingan
Ramon Llull University, La Salle International School of Commerce and Digital Economy
2 shared publications - Angel Alejandro Juan
Universitat Politècnica de València
1 shared publication - Celia Osorio
Universitat Politècnica de València
1 shared publication
Latest Publications
- 31 January 2025
- Published by Springer Nature
- p. 14-26
Applying Machine Learning in Marketing: An Analysis Using the NMF and K-Means Algorithms
- 31 January 2025
- Published by Springer Nature
- p. 14-26
Applying Machine Learning in Marketing: An Analysis Using the NMF and K-Means Algorithms
- Open Access
- 22 June 2024
- Published by MDPI AG in Information
- Vol. 15 (7) , 368
Applying Machine Learning in Marketing: An Analysis Using the NMF and k-Means Algorithms
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.
- 22 June 2024
- Published by MDPI AG in Information
- Vol. 15 (7) , 368
Open AccessApplying Machine Learning in Marketing: An Analysis Using the NMF and k-Means Algorithms
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.