Intelligent Data Processing and Management: Technologies and Applications
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 20 April 2025 | Viewed by 229
Special Issue Editors
Interests: spatial-temporal data management; graph data analysis; big data analytics; stream processing and uncertain data management
Special Issues, Collections and Topics in MDPI journals
Interests: graph data processing; distributed data processing; database systems
Special Issues, Collections and Topics in MDPI journals
Interests: graph data processing; graph data analysis
Special Issue Information
Dear Colleagues,
In the era of big data and artificial intelligence (AI), the efficient processing and management of vast, complex, and continuously growing datasets have become critical challenges for both academia and industry. Rapid advancements in machine learning, data mining, cloud computing, and distributed systems are transforming the landscape of data processing and management, allowing intelligent systems to handle large-scale data more effectively. However, the massive scale and complex variety in today’s data not only present significant challenges in scalability, security, efficiency, and accuracy but also create opportunities to leverage intelligent methods for deeper insights and innovation. This Special Issue seeks to present cutting-edge research that addresses these challenges by exploring innovative approaches to data processing, management techniques, and the integration of intelligent systems to optimize the entire data lifecycle. It will showcase recent advancements and applications in intelligent data processing, offering a comprehensive review of current approaches, methodologies, and technologies that address the complexities of modern data management.
We invite the submission of original research contributions in, but not limited to, AI-powered big data processing, AI-based data mining, intelligent data stream systems, AI-enhanced data security and privacy, AI-driven database systems, large language models (LLMs) in data management, graph data processing, spatial and temporal data analysis, scalable machine learning algorithms, advanced data mining techniques, and the application of modern techniques in data management. These advancements promise to reshape the field of data science, leading to more efficient and intelligent systems for the future.
Prof. Dr. Wenjie Zhang
Dr. Zhengyi Yang
Dr. Long Yuan
Dr. Peng Cheng
Guest Editors
Manuscript Submission Information
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Keywords
- AI-driven data processing
- big data analytics
- machine learning for data management
- scalable machine learning algorithms
- intelligent data stream systems
- AI-enhanced data security
- AI-powered database systems
- large language models (LLMs) in data management
- graph data processing
- spatial and temporal data analysis
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