Systems and methods for dynamically generating groups of received textual data for collective labeling

A method, comprising:

• storing, within a label record database, first data representing a first text string received at a first timestamp;
• querying the label record database to retrieve a plurality of datasets within a plurality of receipt ranges based on the first timestamp for the first data, wherein the plurality of datasets are associated with respective pre-existing labels;
• inputting the first data and a dataset corresponding to a receipt range for the first data based on the first timestamp from the plurality of datasets into an artificial intelligence model to determine a similarity metric;
• and
• storing, in the label record database, based on the similarity metric, a first pre-existing label of second data in the dataset having a second timestamp within the receipt range as a label for the first data.

One or more non-transitory, computer-readable media storing one or more computer program instructions that, when executed by one or more processors, effectuate one or more operations comprising:

• querying a database based on a first timestamp that first data was received to retrieve a dataset associated with one or more respective labels;
• inputting the first data and the dataset into an artificial intelligence model to generate a score;
• and
• assigning, as a first label for the first data, a second label of second data in the dataset based on the score.