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Search engine use of neural network regressor for multi-modal item recommendations based on visual semantic embeddings

  • David A Forsyth (Inventor)
  • , Ranjitha Kumar (Inventor)
  • , Krishna Dusad (Inventor)
  • , Kedan Li (Inventor)
  • , Mariya I Vasileva (Inventor)
  • , Bryan Plummer (Inventor)
  • , Yuan Shen (Inventor)
  • , Shreya Rajpal (Inventor)

Research output: Patent

Abstract

A search engine server includes a communication interface through which to receive a multi-modal query from a browser of a client device, the multi-modal query including at least a first image of an item. A processing device, coupled to the communication interface, is to: execute a neural network (NN) regressor model on the first image to identify a plurality of second items that are similar to and compatible with the item depicted in the first image, wherein a set of images correspond to the plurality of second items; generate structured text that explains, within one of a phrase or a sentence, why the set of images are relevant to the item; and return, to the browser of the client device via the communication interface, a set of search results comprising the set of images and the structured text.
Original languageEnglish (US)
U.S. patent number12131365
Filing date3/24/20
StatePublished - Oct 29 2024

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