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Journal of Knowledge Management and Artificial Intelligence
An International Journal
               
 
 
 
 
 
 
 
 
 
 
JKMAI Home

SSN   2636-395X (print)   
ISSN   2636-3968  (online) 

Editor-in-Chief:  Abdalmuttalb Alsartawy,

Frequency: 3 issues annually 

 

The Journal of Knowledge Management and Artificial Intelligence (JKMAI) is a scholarly publication dedicated to exploring the intersection of knowledge management (KM) and artificial intelligence (AI). The journal’s scope involves all areas and systems empowered by AI for Knowledge Management. As both Artificial Intelligence and Knowledge Management are adamantly bound up with the natures of knowledge and of learning, recent advances in AI can transform KM all the while contributing to the achievement of the Sustainable Development Goals (SDGs). This interdisciplinary journal serves as a platform for researchers, practitioners, and academicians to share their insights, theories, methodologies, and practical applications in these fields.

JKMAI aims to foster a deeper understanding of how knowledge management and AI can mutually benefit and enhance each other. It covers a wide range of topics, including but not limited to knowledge representation and reasoning, intelligent systems, data mining, natural language processing, machine learning, expert systems, knowledge acquisition, and decision support systems.

The journal welcomes original contributions such as refereed research articles, review papers, case studies, survey articles, and technical notes that contribute to the advancement of KM and AI. Submissions undergo a rigorous peer-review process to ensure the quality, relevance, and validity of the published work. Articles published in JKMAI must meet the highest quality standards, as measured by originality and significance of the contribution, and the clarity of exposition. Papers should describe work that has knowledge, practical and theoretical significance. 

By bridging the gap between knowledge management and AI, the JKMAI seeks to address challenges and explore opportunities in leveraging AI technologies to enhance knowledge creation, storage, retrieval, sharing, and utilization. There are two complementary orientations which this platform calls for. First knowledge management, which is directly concerned with managing knowledge in organizations, and second AI which focus on developing systems that can impersonate human knowledge and learning activities. JKMAI therefore encourages the exploration of innovative approaches, methodologies, and tools that can facilitate effective knowledge management processes in various domains and industries.

The readership of the JKMAI includes researchers, professionals, and students interested in knowledge management, AI, information systems, computer science, and related fields. The journal provides a valuable resource for staying updated on the latest advancements, trends, and best practices in the integration of knowledge management and AI. Through its comprehensive coverage, the JKMAI aims to contribute to the development and dissemination of knowledge management practices that harness the power of AI, leading to improved decision-making, innovation, competitive advantage, and organizational performance.

Aim and Scope

The Journal of Knowledge Management and Artificial Intelligence serves as a premier platform for the exchange of ideas, research findings, and practical applications at the intersection of knowledge management and AI. All applications of AI for knowledge management in various industries are welcomed.

Therefore, while peer reviewed original research articles are the Journals key function, JKMAI publishes a variety of other content to advance research on and discourse about KM and AI practices:

·      Double-Blind peer-reviewed articles

·      Case studies

·      Technical notes

·      Commentaries

·      Special Issues where submissions are edited by Guest Editors.

·      Editorials by Guest Editors of Special Issues.

JKMAI facilitates collaboration, knowledge sharing, and the advancement of these fields, ultimately contributing to the development of intelligent systems that enhance organizational knowledge processes as well as sustainable development. The journal aims to provide a platform for researchers, practitioners, and academicians to disseminate their original research, innovative ideas, and practical experiences related to the intersection of knowledge management and AI.

JKMAI mainly contributes to the following Sustainable Development Goals, but not limited to:

 

 

The purpose of JKMAI is twofold. The Journal aims to provide a space for discourse that connects debates about all areas and systems empowered by AI for Knowledge Management practices. Additionally, the Journal aims to highlight how this discourse is reshaping academia as well as industries, government policies, society, expertise, methods, strategies, concepts, and knowledge. The journal is interdisciplinary and therefore welcomes contributions from diverse disciplines, such as computer science, information systems, engineering, business management, management information systems, ethics, governance, accountability, sustainable finance, cognitive sciences, and other related fields.

 

Both academics and professionals will find JKMAI to be a comprehensive source of innovative material.

 

The scope of JKMAI encompasses a wide range of topics related to all areas in knowledge management and AI, including but not limited to:

 

  • Techniques and methodologies for representing, acquiring, and organizing knowledge to enable effective knowledge management and AI applications.
  • Algorithms and approaches for discovering patterns, trends, and insights from large datasets, with a focus on knowledge extraction and knowledge-driven decision making.
  • History, Eras, theory, future of AI and KM.
  • Applications of AI for Sustainable Development Goals
  • Methods for retrieving relevant knowledge and information from diverse data sources, including structured and unstructured data, using AI techniques such as natural language processing and machine learning.
  • Development and deployment of intelligent systems that leverage knowledge representation and reasoning to support decision making, problem-solving, and knowledge sharing.
  • Applications of AI and knowledge management techniques to the development and utilization of the semantic web, ontologies, and knowledge graphs for effective information integration and knowledge sharing.
  • Exploration of AI techniques inspired by human cognition, such as machine learning, deep learning, neural networks, and cognitive architectures, to enhance knowledge management processes and systems.
  • Strategies, models, and technologies for facilitating knowledge transfer, sharing, and collaboration within organizations and across different communities of practice.
  • Examination of governance, ethical, legal, and social considerations associated with the use of AI in knowledge management, including privacy, security, accountability, bias, and fairness.
  • Islamic Knowledge Management perspectives.
  • Application of Artificial Intelligence (AI) in Islamic Finance and Banking.
  • Knowledge Interoperability and AI/Machine Learning.
  • Applications of Machine Learning and Deep learning for Knowledge Management.
  • Applications of AI for organizational KM/ Intellectual Capital KM/Tacit KM/Enterprise KM
  • Sustainable Finance, Sustainable Investment, Sustainable Technology, Sustainable KM.
  • Implications, challenges, and applications of AI and KM techniques for transitioning to Industry 5.0., Society 5.0., and the Metaverse.

JKMAI encourages both theoretical and applied research contributions, as well as case studies, survey articles, technical notes and practical implementations that demonstrate the effective integration of knowledge management and AI in real-world contexts. The journal seeks to bridge the gap between academia and industry by fostering collaborations and facilitating the exchange of ideas that can drive innovation, achieve sustainability, and improve organizational performance through effective knowledge management and AI applications. 

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