Solution recommendation based on incomplete data sets

This invention describes a computer system that helps solve problems by looking at incomplete information. It takes messy data, understands its meaning using a technique called latent semantic indexing, and then matches it to known problem types to suggest solutions. The system is specifically designed to help identify workflows for a printing process.

Why it matters: Filed before the widespread adoption of advanced machine learning and large language models, the semantic analysis and classification components, particularly for incomplete data, are now far more sophisticated and accessible. The challenge of transforming incomplete data into a semantically rich format is significantly easier today.

Status: ExpiredProtection ended and was never renewed
How hard to build: SpecializedSoftware logic, data processing, semantic indexing

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