Elsevier B.V.
+1
1872-7409
Bi-Monthly
7.2
0950-7051
1987
31204853911
Netherlands The
English
YES
Google Scholar
P2PhelpdeskUS@Elsevier.com
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. 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
Learning with inexact supervision, rather than definite labels, has been proposed to relieve the labeling burden. Pairwise comparison (Pcomp) is a novel inexact supervision setting for binar...
COVID-19, caused by SARS-CoV2 infection, varies greatly in its severity but presents with serious respiratory symptoms with vascular and other complications, particularly in older adults. Th...
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