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Systems and methods for recommending cold-start items on a website of a retailer

  • US 10,552,891 B2
  • Filed: 01/31/2017
  • Issued: 02/04/2020
  • Est. Priority Date: 01/31/2017
  • Status: Active Grant
First Claim
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1. A system comprising:

  • one or more processing modules; and

    one or more non-transitory storage modules storing computing instructions configured to run on the one or more processing modules and perform acts of;

    training, using a historical traffic pattern of a plurality of items on a website of an online retailer, one or more first models to recommend one or more first items of the plurality of items for sale on the website of the online retailer after a user has had an interaction on the website of the online retailer with one or more second items of the plurality of items;

    determining static features common to both the one or more first items and the one or more second items;

    training, using the static features of the one or more first items and the one or more second items, a second model to determine whether to coordinate a display of any new item as one of one or more recommended items with any of the plurality of items;

    determining, using the second model and one or more static features of the new item, whether to coordinate a display of the new item as one of the one or more recommended items when one or more of the plurality of items are displayed on the website of the online retailer; and

    coordinating the display of the new item as the one of the one or more recommended items when the one or more of the plurality of items are displayed on the website of the online retailer based on using the second model and the one or more static features of the new item.

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