Abstract: A system including a processor and non-transitory computer-readable media storing computing instructions that, when executed on the processor, perform a method that includes training a machine learning model by using a training data set to determine taxonomy embeddings for taxonomies based on training features that include a context word vector, a center word vector, and a probability. The probability corresponds to a function between the context word vector and the center word vector. The taxonomy embeddings represent at least a first level of a taxonomy and a second level of the taxonomy. The machine learning model, as trained, is used to determine the taxonomy embeddings based on taxonomy identifiers and reduce the taxonomy embeddings by removing at least one taxonomy of the taxonomies that are below a threshold to thereby reduce the taxonomies. The threshold comprises a number of aggregate page views.

Abstract: A system including one or more processors and one or more non-transitory computer readable media storing computing instructions that, when executed on the one or more processors, perform: receiving a taxonomy identifier corresponding to a taxonomy for a product; determining taxonomy embeddings based on the taxonomy identifier, the taxonomy embeddings representing at least a first level of the taxonomy and a second level of the taxonomy; modifying taxonomies based on a threshold to reduce a number of the taxonomy embeddings in subsequent processing; and mapping the taxonomies, as modified, to publisher placements to display the product within the taxonomies on a graphical user interface (GUI).

Abstract: A system including one or more processors and one or more non-transitory computer readable media storing computing instructions that, when executed on the one or more processors, perform: receiving a taxonomy identifier corresponding to a taxonomy for a product; determining taxonomy embeddings based on the taxonomy identifier, the taxonomy embeddings representing at least a first level of the taxonomy and a second level of the taxonomy; modifying taxonomies based on a threshold to reduce a number of the taxonomy embeddings in subsequent processing; and mapping the taxonomies, as modified, to publisher placements to display the product within the taxonomies on a graphical user interface (GUI).