Importance

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Abstract

Various methods and systems for training and utilizing machine learning models for tracking a luggage item of a passenger are disclosed. Representative systems may include custom computer architecture for operating a machine learning model utilizing a plurality of reference indicator data sets obtained from a first B-Type message used to train the machine learning model to determine a routine route and a plurality of reference indicator data sets from a second B-Type message used to train the machine learning model to determine a non-routine route relative to the routine route. The model may match first travel information of a passenger name and an International Air Transport Association (IATA) license plate number for a luggage item of a passenger in a manifest with second travel information from a created B-Type message comprising a reference indicator representative of a non-routine routed luggage item and generate delivery instruction of the luggage item.

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First Claim