Region-specific image download probability modeling

A system for prioritizing a set of images identified as responsive to an image search query from a user based on features of the images identified as relevant to a geographic region of the user, the system comprising:

• a memory comprising:
• a first set of training images;
• a second set of training images;
• regional download data identifying a number of downloads of each of the second set of training images in each of the plurality of geographic regions;
• and
• a computer-operated convolutional neural network;
• and
• a processor configured to:
• provide the first set of training images to the convolutional neural network, wherein upon processing the first set of training images the convolutional neural network is configured to identify features from an image by analyzing pixel data of the image;
• provide the second set of training images to the convolutional neural network and the regional download data identifying a number of downloads of each of the second set of training images in each of the plurality of geographic regions, wherein upon processing the second set of training images and the regional download data the convolutional neural network is configured to analyze image pixel data for each of a plurality of images to identify features, in each of the plurality of images, influencing download probability of the corresponding image in the plurality of geographic regions;
• submit the plurality of images to the convolutional neural network;
• and
• receive, from the neural network and for each of the plurality of images, a download probability of each image for each of the plurality of geographic regions.

A non-transitory machine-readable storage medium comprising machine-readable instructions for causing a processor to execute a method for prioritizing a set of images identified as responsive to an image search query from a user based on features of the images identified as relevant to a geographic region of the user, comprising:

• providing a first set of training images to a convolutional neural network, wherein upon processing the first set of training images the convolutional neural network is configured to identify features from an image by analyzing pixel data of the image;
• providing a second set of training images to the convolutional neural network and regional download data identifying a number of downloads of each of the second set of training images in each of a plurality of geographic regions, wherein upon processing the second set of training images and the regional download data the convolutional neural network is configured to analyze image pixel data for images to identify features, in each of the images, influencing the download probability of the corresponding image in the plurality of geographic regions;
• submitting a plurality of images to the computer-operated convolutional neural network;
• and
• receiving, from the neural network and for each of the plurality of images, a download probability of each image for each of the plurality of geographic regions.