KSEM 2023: The 16th International Conference on Knowledge Science, Engineering and Management
August 16-18, 2023, Guangzhou, China
https://www.ksem2023.conferences.academy/
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Important Dates
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Paper submission: April 28, 2023
Author notification: May 25, 2023
Camera-Ready: June 11, 2023
CALL FOR PAPERS
The aim of this interdisciplinary conference is to provide a forum for researchers in the broad areas of knowledge science, knowledge engineering, and knowledge management to exchange ideas and to report state of the art research results. KSEM is in the list of CCF (China Computer Federation) recommended Conferences (C series, Artificial Intelligence). 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:
第16屆知識科學,、工程與管理國際會議(KSEM 2023)將于8月16-18日在廣州召開,。KSEM系列會議由陸汝鈐院士創(chuàng)辦,,被中國計算機學會推薦為C類會議,,目前已舉辦十五屆。KSEM系列會議的主要目的是為人工智能相關領域的研究人員提供一個論壇,,用來交流人工智能領域相關人員的最新想法和報告最新研究成果,。會議征稿的主題包括但不限于以下內(nèi)容:
Knowledge Science
• Knowledge representation and reasoning
• Formal analysis of knowledge and reasoning about knowledge
• Knowledge complexity and knowledge onotonic reasoning
• 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 Management
• Knowledge management best practices and applications
• Knowledge verification and validation (e.g. Blockchain)
• Knowledge protection and anomaly detection
• Smart knowledge and resource optimization
• Knowledge dissemination
• Knowledge management systems
• Knowledge and data integration
• Knowledge adaptation
• Knowledge creation and acquisition
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