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The Knowledge-Based Systems journal (ISSN: 0950-7051) is an international, peer-reviewed journal published by Elsevier. It focuses on systems that use artificial intelligence methodologies to solve complex, knowledge-intensive problems across science, engineering, and management. This guide provides authors and research administrators with a verified reference for the journal’s scope, publishing model, editorial workflow, indexing metrics, and comparative positioning alongside peer venues.
What It Is
Knowledge-Based Systems publishes original research on the construction, evaluation, and application of intelligent systems. Digital object identifiers for the journal are prefixed by 10.1016/j.knosys and registered with Crossref. The journal bridges foundational artificial intelligence theory and practical knowledge engineering.
At the center of the journal’s domain is the technical concept of a knowledge-based system (KBS). In computer science and artificial intelligence, a knowledge-based system is software that solves complex problems by combining two distinct components:
- Knowledge Base: A structured repository containing domain facts, rules, constraints, ontologies, and heuristic relationships.
- Inference Engine: A reasoning mechanism that applies logical rules or probabilistic algorithms to the knowledge base to deduce conclusions, diagnoses, or decisions.
Unlike purely statistical predictive models, knowledge-based architectures emphasize explicit reasoning and domain knowledge integration. Real-world examples of knowledge bases include medical diagnosis rule bases in clinical decision support, fault-isolation expert systems in aerospace maintenance, supply-chain constraint databases, and semantic knowledge graphs.
Who Runs It and What It Covers
The journal is owned and published by Elsevier BV. Bibliographic records in OpenAlex and Crossref document over 14,000 registered articles across the journal’s history. Its editorial operations focus on automated reasoning, machine learning, and knowledge engineering.
Core Research Scope
The journal invites research encompassing theoretical advances and empirical implementations. Key areas include:
- Knowledge representation, automated reasoning, and ontology engineering.
- Fuzzy systems, rough sets, and belief rule-based reasoning under uncertainty.
- Neuro-symbolic computation and the integration of deep learning with explicit knowledge bases.
- Multi-agent decision systems and distributed knowledge graphs.
- Practical applications in industrial automation, medical decision support, and intelligent software.
Publishing Model and Fees
Knowledge-Based Systems operates as a hybrid journal, offering authors two publication pathways:
- Subscription: Authors publish without submission fees or page charges. Published articles are accessible to institutional subscribers through ScienceDirect, with standard author self-archiving rights.
- Gold Open Access: Authors may choose immediate open access under a Creative Commons license (such as CC BY or CC BY-NC-ND) upon payment of an Article Processing Charge (APC) of $3,430 USD (or €3,210 EUR / £2,750 GBP / ¥425,420 JPY, excluding local taxes).
Because the journal uses a hybrid model rather than pure open access, it is not indexed in the Directory of Open Access Journals (DOAJ), which exclusively lists fully open-access journals.
Peer Review and Editorial Standards
The journal operates a single-anonymized peer review model. Reviewers know author identities and institutional affiliations, while referee identities remain anonymous. Submissions and referee assignments are managed through Elsevier’s online Editorial Manager system.
How to Search, Access, and Submit Articles
Navigating the journal’s literature and submission workflow involves eight key steps:
- Literature Discovery: Published papers can be searched directly on ScienceDirect by keyword, author, or DOI, or located through bibliographic citation databases.
- Scope and Fit Verification: Authors review recent issues to ensure their manuscript contributes novel knowledge engineering or reasoning architectures rather than routine algorithmic benchmarking.
- Manuscript Preparation: Submissions must follow the Elsevier Guide for Authors, including structured abstracts, concise research highlights (3 to 5 bullets), and a formal CRediT author statement.
- Submission via Editorial Manager: Manuscripts are uploaded through the journal’s Editorial Manager platform (see our comparison of Editorial Manager vs ScholarOne vs OJS).
- Editorial Screening: The editorial office screens submissions for scope, presentation, and text originality via Crossref Similarity Check.
- Peer Review: Submissions passing screening are reviewed by two or more independent expert referees, resulting in recommendations of acceptance, revision, or rejection.
- Publishing Agreement: Upon formal acceptance, the corresponding author selects between subscription publication (zero author fee) and gold open access (APC payment).
- Production and Indexing: Accepted papers receive a Crossref DOI and are indexed across global abstracting systems.
Strengths and Limits
Evaluating Knowledge-Based Systems as a venue involves balancing key advantages and constraints:
Strengths
- High Citation Visibility: The journal maintains strong global reach, reflected in an OpenAlex 2-year mean citedness of 7.34 and an h-index of 224 across more than 14,000 articles.
- Consistent Q1 Standing: Ranked in Quartile 1 across computer science and artificial intelligence categories in Scopus and Web of Science.
- No Mandatory Author Fees: The traditional subscription track allows researchers without open-access grant funding to publish at zero cost.
- Broad Application Reach: Articles achieve visibility across engineering, artificial intelligence, and decision sciences.
Limits
- Subscription Paywall: Non-open-access articles require institutional subscriptions to access via ScienceDirect.
- Substantial Open Access Fee: Authors mandated by funders (such as Plan S) to publish open access must pay the $3,430 USD APC.
- Turnaround During Revisions: Competitive submission volumes can extend multi-round review timelines.
Alternatives: Comparative Journal Landscape
Researchers evaluating Knowledge-Based Systems frequently consider alternative journals in artificial intelligence and knowledge engineering. The table below presents verified data from primary bibliographic sources, comparing publisher, access model, APC, and citation metrics:
| Journal | Publisher | Access Model | APC (USD) | 2-Yr Mean Citedness | h-Index |
|---|---|---|---|---|---|
| Knowledge-Based Systems | Elsevier | Hybrid | $3,430 | 7.34 | 224 |
| Journal of Artificial Intelligence Research (JAIR) | AI Access Foundation | Diamond Open Access | $0 | 7.13 | 170 |
| Expert Systems with Applications | Elsevier | Hybrid | $3,500 | 8.55 | 356 |
| Artificial Intelligence | Elsevier | Hybrid | $4,260 | 4.80 | 307 |
| IEEE Transactions on Knowledge and Data Engineering | IEEE Computer Society | Hybrid | $2,645 | 12.55 | 274 |
When selecting among these venues, researchers should weigh publication model alongside citation metrics. Authors prioritizing non-commercial, zero-APC open access often prefer JAIR. Those with applied industrial systems frequently target KBS or Expert Systems with Applications, while data-engineering research often aligns with IEEE TKDE (see our database comparison in Scopus vs Web of Science vs OpenAlex).
Frequently Asked Questions
What are knowledge-based systems?
Knowledge-based systems are artificial intelligence applications that solve complex problems by applying explicit domain knowledge. They combine a structured knowledge base (containing facts, rules, or ontologies) with an inference engine that reasons over the stored knowledge to reach conclusions or provide automated guidance.
What is a knowledge base example?
Prominent examples of knowledge bases include medical diagnosis rule bases used in clinical decision support, equipment troubleshooting trees in aviation maintenance, supply-chain constraint tables, and semantic knowledge graphs such as Wikidata and biomedical ontologies.
Is Knowledge-Based Systems a Q1 journal?
Yes. Knowledge-Based Systems is ranked in Quartile 1 (Q1) within computer science and artificial intelligence categories in Scopus and Clarivate Web of Science (Science Citation Index Expanded). This quartile ranking indicates that its citation impact ranks in the top 25% of journals in its field.
Is JAIR a good journal?
Yes. The Journal of Artificial Intelligence Research (JAIR), established in 1993 by the AI Access Foundation, is widely recognized as one of the premier academic journals in computer science. JAIR operates as a diamond open-access journal, providing peer-reviewed research across all branches of AI without subscription paywalls or author-facing publishing fees.
Does Knowledge-Based Systems charge submission fees?
No. Knowledge-Based Systems charges no submission fees. Authors only pay a fee if they choose the optional gold open access pathway upon acceptance, which incurs an Article Processing Charge (APC) of $3,430 USD. The standard subscription route carries no author charge.
Sources
- Crossref Metadata API: Knowledge-Based Systems (ISSN 0950-7051), records accessed 2026-11-07. https://api.crossref.org/journals/0950-7051
- OpenAlex Bibliographic Database: Source Record for Knowledge-Based Systems (Source ID s144211110), retrieved 2026-11-07. https://openalex.org/sources/s144211110
- Journal of Artificial Intelligence Research (JAIR): Policy and Editorial Structure, retrieved 2026-11-07. https://www.jair.org/index.php/jair/about
- Directory of Open Access Journals (DOAJ): Journal Record for JAIR, accessed 2026-11-07. https://doaj.org/api/search/journals/issn:1076-9757
- NISO Z39.106-2023: Standard Terminology for Peer Review, National Information Standards Organization.
