Classification of dangerous goods via machine learning

This invention describes a computer system that uses a neural network to figure out if an item is a dangerous good based on its text description. Uniquely, the system also identifies which specific words or phrases in the description were most important for that decision, by splitting the text and evaluating the impact of each part.

Why it matters: Filed just before the widespread adoption of advanced large language models. The claims' focus on identifying impactful text segments aligns with current explainable AI techniques, which are now more accessible and powerful.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedSoftware logic, machine learning, neural network

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