Aims
Aims and Scope
The Journal of Artificial Intelligence and Big Data is dedicated to publishing cutting-edge research at the intersection of AI, machine learning, and large-scale data analytics. The journal promotes innovative methodologies and applications that transform data into actionable insights.
Scope covers:
- Machine learning and deep learning
- Big data analytics and data mining
- Natural language processing
- Computer vision and pattern recognition
- AI ethics and responsible AI
- Reinforcement learning
- Knowledge graphs and semantic web
- Edge computing and IoT analytics
- Data visualization and interpretability
- AI applications in healthcare, finance, and science
The journal publishes original algorithms, system architectures, empirical studies, and comprehensive reviews that advance AI and big data technologies.
Scope
The journal covers a broad range of topics including, but not limited to:
Original Research
High-quality empirical studies that present novel findings and advance understanding in the field.
Review Articles
Comprehensive syntheses of existing literature that identify trends and future directions.
Methodological Papers
Innovations in research methods, techniques, and analytical approaches.
Case Studies
In-depth analyses of specific instances that provide valuable insights.
Article Types
Research Article
Review Article
Short Communication
Case Report
Methodology
Letter to Editor
Editorial
Commentary
Target Audience
- Researchers and Academics
- Educators and Students
- Industry Professionals and Practitioners
- Policy Makers and Government Agencies
- Libraries and Information Centers