Abstract: Disclosed herein are systems and methods for correlating item data. A system for correlating item data may comprise a memory storing instructions and at least one processor configured to execute instructions to perform operations comprising: receiving reference text data associated with a reference item from a device; receiving reference image data associated with the reference item from the remote device; determining candidate text data and candidate image data associated with at least one candidate item; selecting a text correlation model; determining a first similarity score by applying the text correlation model to the reference text data and the candidate text data; selecting an image correlation model; determining a second similarity score by applying the image correlation model to the reference image data and the candidate image data; calculating a confidence score based on the first and second similarity scores; and performing a responsive action based on the calculated confidence score.

Abstract: Systems and methods for correlating item data are disclosed. A system for correlating item data may include a memory storing instructions and at least one processor configured to execute instructions to perform operations including: receiving text and image data associated with a reference item from a remote device; converting, using a computer-modeled embedding layer, at least one image to an image embedding; comparing the image embedding to reference embeddings stored in a database; selecting a subset of the candidate item text as candidate text data based on the comparison; selecting a subset of the candidate item images as candidate image data based on the comparison; selecting a text correlation model; determining a first similarity score; selecting an image correlation model; determining a second similarity score; calculating a confidence score based on the first and second similarity scores; and performing a responsive action based on the calculated confidence score.

Abstract: Disclosed herein are systems and methods for correlating item data. A system for correlating item data may comprise a memory storing instructions and at least one processor configured to execute instructions to perform operations comprising: receiving reference text data associated with a reference item from a device; receiving reference image data associated with the reference item from the remote device; determining candidate text data and candidate image data associated with at least one candidate item; selecting a text correlation model; determining a first similarity score by applying the text correlation model to the reference text data and the candidate text data; selecting an image correlation model; determining a second similarity score by applying the image correlation model to the reference image data and the candidate image data; calculating a confidence score based on the first and second similarity scores; and performing a responsive action based on the calculated confidence score.

Abstract: Systems and methods for correlating item data are disclosed. A system for correlating item data may include a memory storing instructions and at least one processor configured to execute instructions to perform operations including: receiving text and image data associated with a reference item from a remote device; converting, using a computer-modeled embedding layer, at least one image to an image embedding; comparing the image embedding to reference embeddings stored in a database; selecting a subset of the candidate item text as candidate text data based on the comparison; selecting a subset of the candidate item images as candidate image data based on the comparison; selecting a text correlation model; determining a first similarity score; selecting an image correlation model; determining a second similarity score; calculating a confidence score based on the first and second similarity scores; and performing a responsive action based on the calculated confidence score.

Abstract: A system for experimentation of e-commerce pricing distribution based on time-interleaving includes one or more processors configured to identifying a first set of items from a plurality of items based on one or more item pricing policies. Scheduling the first set of items to be published on a website during a first time slot from a plurality of time slots by applying a scheduling algorithm. Identifying a first subset of substitutable items and a second subset of substitutable items from the first set of items based on one or more item substitution rules. Assigning the first subset of substitutable items with a first pricing policy and the second subset of substitutable items with a second pricing policy. Publishing the first subset of substitutable items and the second subset of substitutable items. Determining pricing distribution data based on monitoring customer interaction.

Abstract: Disclosed herein are systems and methods for correlating item data. A system for correlating item data may comprise a memory storing instructions and at least one processor configured to execute instructions to perform operations comprising: receiving reference text data associated with a reference item from a device; receiving reference image data associated with the reference item from the remote device; determining candidate text data and candidate image data associated with at least one candidate item; selecting a text correlation model; determining a first similarity score by applying the text correlation model to the reference text data and the candidate text data; selecting an image correlation model; determining a second similarity score by applying the image correlation model to the reference image data and the candidate image data; calculating a confidence score based on the first and second similarity scores; and performing a responsive action based on the calculated confidence score.