Cause Estimation via Knowledge Graph

ChangeBridge: Patent Apps - AI & Computing (G06N)

Published April 2nd, 2026

Detected April 3rd, 2026

Summary

The USPTO published Fujitsu Limited's patent application US20260094031A1 for a cause estimation method using knowledge graphs. The invention selects nodes similar to phenomena requiring cause analysis, generates sub-knowledge graphs by tracing causal relationships, and determines confidence levels to identify cause candidates. The application (Filing Date: 2025-09-23) covers AI-based causal reasoning technology in the G06N classification.

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What changed

USPTO published Fujitsu Limited's patent application for a cause estimation method that uses knowledge graphs to identify potential causes of phenomena. The invention involves selecting nodes similar to a target phenomenon, tracing causal paths from these nodes to potential cause nodes, generating sub-knowledge graphs, and determining confidence levels based on node similarity. The application claims priority to Japanese Application 19336986.

Patent applications do not impose compliance obligations on third parties. Technology companies and AI developers may review this application to understand Fujitsu's approach to causal reasoning via knowledge graphs, particularly in the G06N5/041 and G06N5/025 classifications. No action is required; this is an informational publication of a pending application.

Source document (simplified)

← USPTO Patent Applications

CAUSE ESTIMATION METHOD AND INFORMATION PROCESSING APPARATUS

Application US20260094031A1 Kind: A1 Apr 02, 2026

Assignee

Fujitsu Limited

Inventors

Yoshihiro OKAWA, Tatsuya KIKUZUKI, Masatoshi OGAWA

Abstract

An information processing apparatus selects, out of nodes in a knowledge graph, a first node that is similar to a first phenomenon whose cause is to be estimated. The information processing apparatus generates a sub-knowledge graph including the first node and a second node by tracing from the first node as a starting point to the second node at an end on a cause side of a causal relationship. The information processing apparatus determines a confidence level of the sub-knowledge graph based on a similarity of a first node included in the sub-knowledge graph to a first phenomenon. The information processing apparatus then determines whether to include a third phenomenon indicated by the second node in the sub-knowledge graph in cause candidates of the first phenomenon based on the confidence level of the sub-knowledge graph.