Data Mining and Business Intelligence Trends
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-2902-9_5
Reference40 articles.
1. Agarwal, S. (2013). Data mining: Data mining concepts and techniques. In 2013 International Conference on Machine Intelligence and Research Advancement. IEEE.
2. Barth, J. R. (2015). The first great financial crisis of the 21st century: A retrospective (Vol. 9). World Scientific.
3. Bayer, H., et al. (2017). Big data mining and business intelligence trends. Journal of Asian Business Strategy, 7(1), 23.
4. Bellazzi, R., & Zupan, B. (2008). Predictive data mining in clinical medicine: Current issues and guidelines. International Journal of Medical Informatics, 77(2), 81–97.
5. Božič, K., & Dimovski, V. (2019). Business intelligence and analytics for value creation: The role of absorptive capacity. International Journal of Information Management, 46, 93–103.
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