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KSEM 2024 : 17th International Conference on Knowledge Science, Engineering and Management

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Conference Series : Knowledge Science, Engineering and Management
 
Link: https://ai-edge.net/
 
When Aug 16, 2024 - Aug 18, 2024
Where Birmingham, United Kingdom
Submission Deadline Jan 15, 2024
Notification Due Mar 1, 2024
Final Version Due May 1, 2024
Categories    artificial intelligence   knowledge science   formal ontologies   knowledge graphs
 

Call For Papers

A PDF flyer for the call-for-papers can be downloaded from:
https://ai-edge.net/files/CFPKSEM2024latest.pdf

The conference committee invites submissions of applied or theoretical research as well as of application-oriented papers on all the topics of KSEM. Topics include, but are not limited to the following:

Knowledge Science

• Knowledge representation and reasoning
• Formal analysis of knowledge; reasoning about knowledge
• Knowledge complexity and knowledge metrics
• Uncertainty in knowledge (randomness, fuzziness, roughness, vagueness)
• Knowledge fusion for decision making
• Formal ontologies
• Reasoning about knowledge in the presence of inconsistency, incompleteness and context-dependency
• Belief propagation, revision and aggregation
• Cognitive foundations of knowledge
• Integration of machine learning and knowledge representation
• Knowledge-driven learning
• Knowledge for cognitive robotics
• Knowledge for cognitive analytics
• Knowledge in complex systems (e.g. manufacture assembling, economical and quantum systems)
• Game-theoretical aspects of knowledge; knowledge in multi-agent systems

Knowledge Engineering

• Knowledge modeling
• Knowledge acquisition, such as knowledge modules, temporal knowledge, etc.
• Knowledge extraction from texts/videos, big data/Web
• Knowledge discovery from very large databases
• Knowledge integration
• Knowledge-based software engineering
• Knowledge-based systems in life sciences
• Knowledge-based systems for smart homes
• Conceptual modeling in knowledge-based systems
• Semantic database systems
• Semantic Web: Content and ontological engineering
• Knowledge engineering applications
• Knowledge modeling for digital twins
• Knowledge-based system for Chatbot
• Knowledge-based system and Large Language Models (LLMs)

Knowledge Management

• Knowledge management best practices and applications
• Knowledge verification and validation (e.g. Blockchain)
• Knowledge protection and attack detection
• Knowledge-Based Systems in Cybersecurity Threat Detection and Intelligent Decision-Making
• Smart knowledge and resource optimization
• Knowledge dissemination
• Knowledge management systems
• Knowledge and data integration
• Knowledge adaptation

Knowledge Graphs

• Knowledge graph storage and management
• Probabilistic knowledge graphs
• Knowledge graph construction
• Knowledge graph query
• Learning on knowledge graphs
• Knowledge graph embedding
• Knowledge graph completion
• Multi-modal knowledge graphs
• Knowledge graph applications
• Deep graph neural networks

Related Resources

ACIE 2024   CPS--2024 4th Asia Conference on Information Engineering (ACIE 2024)
Ei/Scopus-AACIP 2024   2024 2nd Asia Conference on Algorithms, Computing and Image Processing (AACIP 2024)-EI Compendex
Ei/Scopus-CISDS 2024   2024 3rd International Conference on Communications, Information System and Data Science (CISDS 2024)
CCVPR 2024   2024 International Joint Conference on Computer Vision and Pattern Recognition (CCVPR 2024)
SI AIMLDE 2024   SPECIAL ISSUE on Applied Artificial intelligence, Machine Learning, and Data Engineering
IEEE-Ei/Scopus-ACEPE 2024   2024 IEEE Asia Conference on Advances in Electrical and Power Engineering (ACEPE 2024) -Ei Compendex
Ei/Scopus- DMCSE 2024   2024 International Conference on Data Mining, Computing and Software Engineering (DMCSE 2024)
IEEE-Ei/Scopus-SGGEA 2024   2024 Asia Conference on Smart Grid, Green Energy and Applications (SGGEA 2024) -EI Compendex
MEDES 2024   The 16th International Conference on Management of Digital EcoSystems
IPM-LLMDQKG 2025   Special issue of Information Processing & Management on Large Language Models and Data Quality for Knowledge Graphs