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Machine Learning Applications in Databases and Big Data Analytics
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AI
DOI：10.1007/978-3-032-06634-3_8.png)
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Abstract
En 中文
The convergence of machine learning (ML) and big data technologies redefines the landscape of data-driven systems, enabling adaptive, scalable, and intelligent solutions across diverse domains. This survey systematically explores the integration of ML techniques in database systems and big data frameworks, highlighting advances in query optimization, data quality assurance, feature engineering, and real-time stream processing. Furthermore, it analyzes real-world applications, including predictive maintenance, recommendation systems, fraud detection, and healthcare analytics, demonstrating the operational value of ML in data-intensive environments. Finally, the survey concludes by identifying key challenges in scalability, interpretability, and privacy-preserving learning, outlining promising research directions to foster the next generation of robust and trustworthy big data analytics.
Keywords:
Databases
Machine Learning
Big Data
Data Processing
Journal
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IF:
0
Papers:
90
Citations:
0