International Conference on Knowledge Engineering using Artificial Intelligence

ICKEAI

5th May – 6th May 2027 Vienna, Austria

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Registration Summary

Conference ICKEAI

Date 5th May – 6th May 2027

Location Vienna, Austria

Participation Type Listener

Organizer Science Leagues

Registration Mode Standard / Physical

Registration Fee USD 0.00

Bank Convenience Charges (5.8%)i USD 0.00

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Total Payable USD 0.00

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Conference Session Tracks

Aligned with UN Sustainable Development Goals

The conference's session tracks effectively support the following SDGs.

01 Advancements in Knowledge Engineering Frameworks +

This track focuses on the latest frameworks and methodologies in knowledge engineering that leverage artificial intelligence. Participants will explore innovative approaches to enhance knowledge representation and system optimization.

SDG 4 SDG 9

02 Machine Learning Applications in Intelligent Systems +

This session will delve into the application of machine learning techniques within intelligent systems. Researchers are invited to present their findings on how these applications can improve decision-making processes.

SDG 8

03 Predictive Analytics in AI-Driven Environments +

This track examines the role of predictive analytics in enhancing AI-driven systems. Discussions will center on methodologies that improve forecasting accuracy and operational efficiency.

SDG 9 SDG 11

04 Data Analytics for Knowledge Discovery +

Focusing on data analytics, this session will highlight techniques that facilitate knowledge discovery from large datasets. Participants will share insights on how data-driven strategies can inform knowledge engineering.

SDG 4 SDG 9

05 Automation and Intelligent Systems Integration +

This track explores the integration of automation technologies with intelligent systems. Presenters will discuss the implications of such integrations for enhancing operational workflows.

SDG 8

06 Deep Learning Techniques in Knowledge Engineering +

This session will investigate the application of deep learning techniques in the field of knowledge engineering. Researchers will present case studies showcasing the effectiveness of deep learning in various AI applications.

SDG 4 SDG 9

07 Semantic Systems and Knowledge Representation +

This track focuses on the development of semantic systems that improve knowledge representation. Participants will explore how semantics can enhance interoperability and knowledge sharing.

SDG 4 SDG 10

08 Innovation Strategies in AI-Driven Knowledge Systems +

This session will address innovative strategies for developing AI-driven knowledge systems. Discussions will include best practices and case studies that demonstrate successful implementations.

SDG 9 SDG 10

09 Optimization Techniques in AI Applications +

This track examines optimization techniques that enhance the performance of AI applications. Researchers will present methodologies that improve efficiency and effectiveness in various domains.

SDG 9

10 Ethical Considerations in AI and Knowledge Engineering +

This session will explore the ethical implications of using artificial intelligence in knowledge engineering. Participants will discuss frameworks for ensuring responsible AI deployment.

SDG 10 SDG 16

11 Future Trends in AI and Knowledge Engineering +

This track will investigate emerging trends and future directions in the intersection of AI and knowledge engineering. Researchers are encouraged to share their visions for the evolution of these fields.

SDG 9 SDG 17