Airport information updates based on machine-learning models

A method comprising:

• receiving, at one or more processors, a data source that includes information associated with one or more airports;
• determining, using a first machine-learning model, a particular classification of the data source and scheduling information associated with the data source;
• allocating, using a second machine-learning model, particular information in the data source to a particular airport, the particular airport associated with a particular database, and the particular information scheduled to be descriptive of a feature of the particular airport;
• generating, using a third machine-learning model, an updated dataset based on the particular information, the updated dataset having a format similar to a current dataset in the particular database, the current dataset indicative of the feature of the particular airport, and the third machine-learning model selected based on the particular classification;
• and
• updating the current dataset in the particular database with the updated dataset based on the scheduling information in response to a user verification.

A non-transitory computer-readable medium comprising instructions that, when executed by one or more processors, cause the one or more processors to:

• receive a data source that includes information associated with one or more airports;
• determine, using a first machine-learning model, a particular classification of the data source and scheduling information associated with the data source;
• allocate, using a second machine-learning model, particular information in the data source to a particular airport, the particular airport associated with a particular database, and the particular information scheduled to be descriptive of a feature of the particular airport;
• generate, using a third machine-learning model, an updated dataset based on the particular information, the updated dataset having a format similar to a current dataset in the particular database, the current dataset indicative of the feature of the particular airport, and the third machine-learning model selected based on the particular classification;
• and
• update the current dataset in the particular database with the updated dataset based on the scheduling information in response to a user verification.