Knowledge-Based Systems

Knowledge-based Systems is an international and interdisciplinary journal in the field of artificial intelligence.

Goal / Target audience
The journal publish original, innovative and creative research results in the field of artificial intelligence, and is designed to focus on research in knowledge-based and other artificial intelligence techniques-based systems with the following objectives and capabilities: to support human prediction and decision-making through data science and computation techniques; to provide a balanced coverage of both theory and practical study in the field; and to encourage new development and implementation of knowledge-based intelligence models, methods, systems, and software tools, with applications in business, government, education, engineering and healthcare.

Publisher
Elsevier

Topics/ Content
This journal’s current leading topics are but not limited to:
 Machine learning theory, methodology and algorithms,
 Data science theory, methodologies and techniques,
 Knowledge presentation and engineering,
 Recommender systems and E-service personalization,
 Intelligent decision support systems, prediction systems and warning systems,
 Computational Intelligence systems,
 Data-driven optimization,
 Cognitive interaction and brain–computer interface,
 Knowledge-based computer vision techniques.

ISSN
09507051

More information
https://www.sciencedirect.com/journal/knowledge-based-systems