Fujitsu’s Causal Knowledge Graph white paper presents a data-driven decision-making approach that integrates causal analysis with knowledge graphs to enhance reasoning under complex conditions. It addresses limitations of large language models, which lack causal understanding and domain-specific reasoning. The approach combines knowledge graphs’ relational structure with causal analysis’ focus on cause-effect relationships, enabling clearer, more accurate insights. Fujitsu’s technology extracts and estimates causal links from diverse data, supporting applications like root cause analysis and decision-making. Case studies in ICT, HR, and healthcare show its value in clarifying complex data for better decisions.

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