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

被引:1
作者
Gallego, Victor [1 ,2 ]
Lingan, Jessica [1 ]
Freixes, Alfons [1 ]
Juan, Angel A. [2 ]
Osorio, Celia [2 ]
机构
[1] Euncet Business Sch, Business Analyt Res Grp, Terrassa 08225, Spain
[2] Univ Politecn Valencia, Res Ctr Prod Management & Engn, Alcoy 03801, Spain
关键词
machine learning; digital marketing; algorithms; artificial intelligence; BIG DATA; ARTIFICIAL-INTELLIGENCE; IMPACT;
D O I
10.3390/info15070368
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页数:16
相关论文
共 50 条
[31]   Prediction of Breast Cancer using Machine Learning Algorithms [J].
Mangal, Anuj ;
Jain, Vinod .
PROCEEDINGS OF THE 2021 FIFTH INTERNATIONAL CONFERENCE ON I-SMAC (IOT IN SOCIAL, MOBILE, ANALYTICS AND CLOUD) (I-SMAC 2021), 2021, :464-466
[32]   Water quality classification using machine learning algorithms [J].
Nasir, Nida ;
Kansal, Afreen ;
Alshaltone, Omar ;
Barneih, Feras ;
Sameer, Mustafa ;
Shanableh, Abdallah ;
Al-Shamma'a, Ahmed .
JOURNAL OF WATER PROCESS ENGINEERING, 2022, 48
[33]   Prediction of Food Production Using Machine Learning Algorithms of Multilayer Perceptron and ANFIS [J].
Nosratabadi, Saeed ;
Ardabili, Sina ;
Lakner, Zoltan ;
Mako, Csaba ;
Mosavi, Amir .
AGRICULTURE-BASEL, 2021, 11 (05)
[34]   Artificial Intelligence in Health Care: Predictive Analysis on Diabetes Using Machine Learning Algorithms [J].
Wadhwa, Shruti ;
Babber, Karuna .
COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2020, PT II, 2020, 12250 :354-366
[35]   Projection and identification of vulnerable areas due to heavy snowfall using machine learning and K-means clustering with RCP scenarios [J].
Song, Moon-Soo ;
Lee, Jae-Joon ;
Yun, Hong-Sic ;
Yum, Sang-Guk .
CLIMATE SERVICES, 2024, 33
[36]   Online CQI-based optimization using k-means and machine learning approach under sparse system knowledge [J].
Shah, Brijesh ;
Dalwadi, Gaurav ;
Pandey, Anupkumar ;
Shah, Hardip ;
Kothari, Nikhil .
INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, 2020, 33 (03)
[37]   COVID-19 Prediction Applying Supervised Machine Learning Algorithms with Comparative Analysis Using WEKA [J].
Villavicencio, Charlyn Nayve ;
Macrohon, Julio Jerison Escudero ;
Inbaraj, Xavier Alphonse ;
Jeng, Jyh-Horng ;
Hsieh, Jer-Guang .
ALGORITHMS, 2021, 14 (07)
[38]   Horizontal Attacks Using K-means: Comparison with Traditional Analysis Methods [J].
Kabin, Ievgen ;
Aftowicz, Marcin ;
Varabei, Yauhen ;
Klann, Dan ;
Dyka, Zoya ;
Langendoerfer, Peter .
2019 10TH IFIP INTERNATIONAL CONFERENCE ON NEW TECHNOLOGIES, MOBILITY AND SECURITY (NTMS), 2019,
[39]   Medical Decision Making Diagnosis System Integrating k-means and Naive Bayes algorithms [J].
Altayeva, Aigerim ;
Zharas, Suleimenov ;
Cho, Young Im .
2016 16TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS), 2016, :1087-1092
[40]   Email Sentiment Analysis Through k-Means Labeling and Support Vector Machine Classification [J].
Liu, Sisi ;
Lee, Ickjai .
CYBERNETICS AND SYSTEMS, 2018, 49 (03) :181-199