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ICMLIS · Registering as Listener

International Conference on Machine Learning and Intelligent Systems

29th Dec – 30th Dec 2026 Kyoto, Japan Standard / Physical Participation

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ConferenceICMLIS

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Conference Session Tracks

SDG-Aligned Research Themes

International Conference on Machine Learning and Intelligent Systems conference tracks support global knowledge exchange, innovation, and sustainable development priorities across diverse disciplines.

SDG 9 - Industry, Innovation and Infrastructure

This track focuses on the methodologies and frameworks for representing knowledge within social science domains. It aims to explore how knowledge representation can enhance understanding and analysis of social phenomena.

This session will delve into the applications of artificial intelligence techniques in the field of linguistics. Participants will discuss innovative approaches to language processing and understanding through AI.

This track examines the role of ontologies in structuring knowledge within the humanities. It will highlight the integration of semantic web technologies to enhance accessibility and interoperability of cultural data.

This session will explore the construction and utilization of knowledge graphs in social research. Emphasis will be placed on their potential to uncover relationships and insights within complex social datasets.

This track investigates the development and application of reasoning systems in social science contexts. It will cover both theoretical frameworks and practical implementations that support decision-making processes.

This session will focus on the design and application of expert systems for analyzing social policies. Discussions will include case studies demonstrating the impact of these systems on policy formulation and evaluation.

This track will highlight the contributions of symbolic AI to the field of linguistic research. It will cover topics such as formal language representation and the implications for natural language understanding.

This session will explore the application of machine learning techniques to address challenges in social sciences. Participants will share insights on data-driven approaches to social phenomena analysis.

This track focuses on the development of conceptual models that facilitate the understanding of social knowledge systems. It aims to bridge theoretical concepts with practical applications in social research.

This session will examine techniques for knowledge discovery within humanities datasets. Participants will discuss innovative methods for extracting meaningful insights from diverse cultural and historical data.

This track will explore the intersection of cognitive computing and social science research. It will highlight how cognitive systems can enhance analytical capabilities and improve understanding of human behavior.