Intelligent System Comparing Clustering Algorithms to Recommend Sales Strategies

Author:

Arévalo-Huaman Gianella,Vallejos-Huaman Jose,Burga-Durango Daniel

Publisher

Springer Nature Switzerland

Reference12 articles.

1. We Need To Talk About E-Commerce: Too Many Digital Brands Are Failing, And We Need New Tools To Help Keep Founders On Track. https://www.forbes.com/sites/forbestechcouncil/2021/07/22/we-need-to-talk-about-e-com-merce-too-many-digital-brands-are-failing-and-we-need-new-tools-to-help-keep-founders-on-track/?sh=736f25871c9c. Accessed 21 Apr 2023

2. La burbuja de las tiendas ‘online’: el 85% cierra antes de cumplir 2 años. https://www.elmundo.es/comunidad-valen-ciana/2016/05/21/57401de422601d252e8b4589.html. Accessed 21 Apr 2023

3. Zhang, B., Wang, L., Li, Y.: Precision marketing method of e-commerce platform based on clustering algorithm. Complexity 2021, Article no. 5538677, 10 p. (2021). https://doi.org/10.1155/2021/5538677

4. Fang, C., Liu, H.: Research and application of improved clustering algorithm in retail customer classification. Symmetry 13(10), 1789 (2021). https://doi.org/10.3390/sym13101789

5. Zhan, M., Gao, H., Liu, H., Peng, Y., Lu, D., Zhu, H.: Identifying market structure to monitor product competition using a consumer-behavior-based intelligence model. Asia Pac. J. Mark. Logist. 33(1), 99–123 (2020). https://doi.org/10.1108/APJML-08-2019-0497

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