Knowledge-Based Systems

Knowledge-Based Systems - ISSN 0950-7051
Source Normalized Impact per Paper (SNIP): 2.606 Source Normalized Impact per Paper (SNIP):
SNIP measures contextual citation impact by weighting citations based on the total number of citations in a subject field.
SCImago Journal Rank (SJR): 1.46 SCImago Journal Rank (SJR):
SJR is a prestige metric based on the idea that not all citations are the same. SJR uses a similar algorithm as the Google page rank; it provides a quantitative and a qualitative measure of the journal’s impact.
Impact Factor: 5.101 (2018) Impact Factor:
The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years.
© 2017 Journal Citation Reports ® (Clarivate Analytics, 2017)
5 Year Impact Factor: 5.358 (2018) Five-Year Impact Factor:
To calculate the five year Impact Factor, citations are counted in 2016 to the previous five years and divided by the source items published in the previous five years.
© 2017 Journal Citation Reports ® (Clarivate Analytics, 2017)
Volumes: Volumes 187-210
Issues: 24 issues
ISSN: 09507051

Institutional Subscription

Sales tax will be calculated at check-out Price includes VAT/GST

Secure Checkout

Personal information is secured with SSL technology.

Free Shipping

Free global shipping
No minimum order.


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