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KnowTrAI 2023 : 1st International Scientific Workshop on AI-driven Knowledge Transformation | |||||||||||||||
Link: https://no-try.org/ | |||||||||||||||
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Call For Papers | |||||||||||||||
Welcome to KnowTrAI 2023, the 1st International Scientific Workshop on AI-driven Knowledge Transformation!
KnowTrAI 2023 will be conducted in conjunction with the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2023). KnowTrAI will take place as a one-day event in a hybrid manner (Rome and online) between November 13 and 15, 2023 (TBA). # Workshop website: https://no-try.org/ # Conference website: https://ic3k.scitevents.org # Submission website: https://ic3k.scitevents.org/KnowTrAI.aspx # Publication in IC3K Conference Proceedings via ScitePress (DBLP indexed) # Post-Publications planned (selected papers): # Springer Nature Computer Science Journal # Springer Book - Communications in Computer and Information Science (CCIS) ################## ## ABOUT ######### ################## In the era of rapid technological advancements, artificial intelligence (AI) has emerged as a catalyst for transforming the way we acquire, process, and apply knowledge. KnowTrAI (pronounced "no try") aims to bring together researchers, industry professionals, AI practitioners, software engineers, educators, trainers, and domain experts to explore the transformative power of AI for redefining the landscape of knowledge, streamlining processes, and empowering individuals with the skills needed to thrive in an ever-evolving world. KnowTrAI 2023 provides a platform for insightful discussions driven by latest research contributions in the field, exchange of ideas, and exploration of cutting-edge advancements, practical implementations, and thought-provoking insights. ################## ## CfP ######### ################## We invite submissions focused on, but not limited to, the following fields: # Technical aspects of AI-driven knowledge transformation # AI-driven redesign of knowledge structures and knowledge processes # AI-driven knowledge transfer and skill development # Case studies and best practices in AI-driven knowledge transformation # Theoretical, methodological, and conceptual aspects of AI-driven knowledge transformation For a more detailed list on the addressed topics and further information, please visit http://no-try.org. |
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