Special Issue "Artificial Intelligence and Data Science"
Deadline for manuscript submissions: 30 April 2024 | Viewed by 10371
Interests: data science; network science; knowledge science; anomaly detection
Data science is the fundamental theory and methodology of data mining. The emergence of artificial intelligence (AI) technology has broadened and deepened data science, which further benefits a variety of applications, including cyber security, fraud detection, healthcare, transportation, etc. Based on a mixture of analysis, modeling, computation, and learning, a hybrid approach integrating AI technology has been proposed to study the process from data to information, to knowledge, and to decision. The development of AI technology will help us clarify the theoretical boundaries and provide new opportunities for the continuous development of data science. At the same time, the development of data science technology and the emergence of new intelligence paradigms will also facilitate the application of AI in many application scenarios.
Although big data and computational intelligence technologies have made great progress in many engineering applications, the theoretical basis and technical mechanism of AI and data science technology are still at an early stage. The single-point breakthrough of either AI or data science can hardly provide sustainable support for big data-driven intelligent applications. The fundamental issues of AI and data science should be considered deeply and urgently. Therefore, this Special Issue aims to enhance or reconstruct the theoretical cornerstones of AI and data science so as to promote the continuous progress and leapfrog development of real-world applications. Specifically, this Special Issue will try to answer the following questions. (1) How to break the boundaries among disciplines, methodologies, and theories to further promote AI and data science technologies? (2) What will be the new paradigm of AI and data science? (3) How can AI and data science technologies further benefit the real-world applications? The topics of interest for this Special Issue address the application of AI and data science methods including, but not limited to:
- Knowledge-driven AI technologies;
- Advanced deep learning approaches such as fairness learning;
- Security, trust, and privacy;
- Few-shot learning, one-shot learning, and zero-shot learning;
- Data governance strategies and technologies;
- Intelligent computing such as auto machine learning, lifelong learning, etc.;
- Urgent applications such as anomaly detection;
- Complexity theory;
- High-performance computing;
- Big data technologies and applications;
- Data analytics and visualization;
- Real-world AI and data science applications such as healthcare, transportation, etc.
Dr. Shuo Yu
Dr. Feng Xia
Manuscript Submission Information
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- artificial intelligence
- data science
- deep learning
- big data
- data mining