Conference Information
KSEM 2021: International Conference on Knowledge Science, Engineering and Management
http://www.cloud-conf.net/ksem21/
Submission Date:
2021-03-15
Notification Date:
2021-06-01
Conference Date:
2021-08-14
Location:
Tokyo, Japan
Years:
14
CCF: c   CORE: b   QUALIS: b3   Viewed: 39070   Tracked: 113   Attend: 39

Conference Location
Call For Papers
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
• Logics of knowledge; formal analysis of knowledge; reasoning about knowledge
• Knowledge complexity and knowledge metrics
• Common sense knowledge; non-monotonic reasoning
• Uncertainty in knowledge (randomness, fuzziness, roughness, vagueness)
• Machine learning
• Formal ontologies
• Integration of machine learning and knowledge representation
• Reasoning about knowledge in the presence of inconsistency, incompleteness and context-dependency
• Belief revision and updates
• Cognitive foundations of knowledge
• Knowledge in complex systems (e.g. economical and quantum systems)
• Game-theoretical aspects of knowledge; knowledge in multi-agent systems

Knowledge Engineering

• Knowledge extraction from texts/big data/Web
• Knowledge discovery from very large databases
• Knowledge integration
• Knowledge-based software engineering
• Knowledge-based systems in life sciences
• Conceptual modelling in knowledge-based systems
• Semantic database systems
• Semantic Web: Content and ontological engineering
• Knowledge engineering applications

Knowledge Management

• Knowledge creation and acquisition
• Knowledge verification and validation
• Knowledge dissemination
• Knowledge management systems
• Knowledge and data integration
• Knowledge adaptation
• Knowledge management best practices and applications

Knowledge Graphs

• Probabilistic Knowledge Graphs
• Knowledge graph construction
• Knowledge graph query
• Knowledge graph storage, query and management
• Learning on knowledge graphs
• Knowledge graph embedding
• Knowledge graph completion
Last updated by Dou Sun in 2020-09-19
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