Knowledge-based Systems is an international and interdisciplinary journal in the field of artificial intelligence. The journal will publish original, innovative and creative research results in the field, 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.
topics of interest
- 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
works as
journal
containing
Large language models as oracles for instantiating ontologies with domain-specific knowledge (2024) — Giovanni Ciatto, Andrea Agiollo, Matteo Magnini, Andrea Omicini