Dynamic classification of time-series categorical data

One or more non-transitory computer-readable media containing instructions that, when executed by one or more processors, cause a system to perform operations, the operations comprising:

• obtaining position data and associated time entries for a plurality of individuals;
• for each of the plurality of individuals:
• associating instances of the position data with categories of locations to generate a context vector, the context vector including text strings describing a context of a given individual;
• and
• squeezing the context vector to combine consecutive categories of locations to generate a count vector, the count vector including the text strings and a count of the consecutive categories of locations;
• classifying each of the plurality of individuals based on a comparison of the count vector to a known class of individuals;
• and
• generating instructions to adjust at least one factor directing flow of a plurality of people in a different manner based on the classification.