Scalable machine learning-driven segmentation system

A system comprising:

• a storage device that stores instructions;
• and
• one or more processors configured by the instructions to perform operations comprising:
• accessing data representing activity on a network site;
• generating, based on the data, a plurality of feature sets representing periods of activeness on the network site;
• forming a subset of the plurality of feature sets by reducing dimensionality of the plurality of feature sets;
• generating a plurality of clusters of the subset of the plurality of feature sets, each cluster being associated with a label representing a different type of activeness on the network site;
• and
• generating a database query set based on the plurality of clusters and the plurality of feature sets to classify one or more activities on the network site into one of the plurality of clusters.

A non-transitory computer-readable medium comprising instructions stored thereon that are executable by at least one processor to cause a computing device to perform operations comprising:

• accessing data representing activity on a network site;
• generating, based on the data, a plurality of feature sets representing periods of activeness on the network site;
• forming a subset of the plurality of feature sets by reducing dimensionality of the plurality of feature sets;
• generating a plurality of clusters of the subset of the plurality of feature sets, each cluster being associated with a label representing a different type of activeness on the network site;
• and
• generating a database query set based on the plurality of clusters and the plurality of feature sets to classify one or more activities on the network site into one of the plurality of clusters.