当前位置: X-MOL首页 › SCI期刊查询及投稿分析系统 › Knowledge-Based Systems杂志
Knowledge-Based Systems
基本信息
期刊名称 | Knowledge-Based Systems KNOWL-BASED SYST |
---|---|
期刊ISSN | 0950-7051 |
期刊官方网站 | https://www.sciencedirect.com/journal/knowledge-based-systems |
是否OA | No |
出版商 | Elsevier B.V. |
出版周期 | Bimonthly |
文章处理费 | 登录后查看 |
始发年份 | |
年文章数 | 874 |
影响因子 | 7.2(2023) scijournal影响因子 greensci影响因子 |
中科院SCI期刊分区
大类学科 | 小类学科 | Top | 综述 |
---|---|---|---|
工程技术2区 | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机:人工智能2区 | 否 | 否 |
CiteScore
CiteScore排名 | CiteScore | SJR | SNIP | ||
---|---|---|---|---|---|
学科 | 排名 | 百分位 | 14.8 | 2.219 | 2.226 |
Decision Sciences Information Systems and Management |
8/148 | 94% |
|||
Business, Management and Accounting Management Information Systems |
8/131 | 94% |
|||
Computer Science Software |
28/407 | 93% |
|||
Computer Science Artificial Intelligence |
31/350 | 91% |
补充信息
自引率 | 9.7% |
---|---|
H-index | 94 |
SCI收录状况 |
Science Citation Index Expanded |
官方审稿时间 | 登录后查看 |
网友分享审稿时间 | 数据统计中,敬请期待。 |
接受率 | 登录后查看 |
PubMed Central (PMC) | http://www.ncbi.nlm.nih.gov/nlmcatalog?term=0950-7051%5BISSN%5D |
投稿指南
期刊投稿网址 | https://www.editorialmanager.com/KNOSYS |
---|---|
收稿范围 | 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 Special Issue Instructions Knowledge-based Systems (KBS), an international and interdisciplinary peer-reviewed academic journal in the field of artificial intelligence, welcomes the submission of special issues on timely topics within the scope of the journal. The main objectives of the journal to organize special issues are to bring together state-of-the-art and high-quality research works, to promote key advances in the science and applications in the important field of knowledge-based systems, and to drive emerging research topics and establish flagships in the field. How to submit your Special Issue proposal: Check the selection criteria below for a KBS special issue to make sure your proposal is relevant to the journal, Write your special issue proposal in the structure given below, Submit the special issue proposal to the Editor-in-Chief (EiC), The EiC and KBS special issue assessment panel will then review your proposal and reply with their decision. Guest Editors' Duty and Special Issue Process: After a special issue proposal is accepted by the journal, a call for papers can be formally distributed. All the papers submitted to the special issue will undergo a peer review process. Guest Editors will manage the process and ensure that the reviewing standards for Knowledge-Based Systems regular issues are maintained. A Managing Guest Editor, who will be responsible for distributing submissions to the other Guest Editors, will need to be nominated. After the Guest Editors make recommendations on each paper in the special issue, the EiC will make the final decisions of acceptance for publication. After all papers to be included in the Special Issue are accepted, the Guest Editors will be responsible for either preparing an Editorial (1–2 pages in length) or writing a field survey (5–10 pages in length), which will incorporate the selected papers and related literature relevant to the topic of the special issue. Reproducibility Badge Initiative and Software Publication Reproducibility Badge Initiative (RBI) is a collaboration with Code Ocean (CO), a cloud based computational reproducibility platform that helps the community by enabling sharing of code and data as a resource for non-commercial use. CO verifies the submitted code (and data) and certifies its reproducibility. Code submission will be verified by the Code Ocean team for computational reproducibility by making sure it runs, delivers results and it is self-contained. For more information please visit this help article. Note that an accepted paper will be published independently of the CO application outcome. However, if the paper receives the Reproducibility badge, it will be given additional exposure by having an attached R Badge, and by being citable at the CO website with a DOI. We invite you to convert your open source software into an additional journal publication in Software Impacts, a multi-disciplinary open access journal. Software Impacts provides a scholarly reference to software that has been used to address a research challenge. The journal disseminates impactful and re-usable scientific software through Original Software Publications which describe the application of the software to research and the published outputs. For more information contact us at: software.impacts@elsevier.com |
收录体裁 | Original high-quality research review papers Short communications |
投稿指南 | https://www.sciencedirect.com/journal/knowledge-based-systems/publish/guide-for-authors |
投稿模板 | |
参考文献格式 | https://www.elsevier.com/journals/knowledge-based-systems/0950-7051/guide-for-authors |
编辑信息 |
|
我要分享 (欢迎您来完善期刊的资料,分享您的实际投稿经验)