Patent ID: 11861675
Assignee: HOME DEPOT PRODUCT AUTHORITY, LLC
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 20:
21. A computer-implemented method, comprising:
determining, by one or more processors of one or more computing devices, first taxonomy data associated with an anchor item, wherein:
the first taxonomy data comprises a plurality of levels for classifying items organized from a highest taxonomy level to a lowest taxonomy level; and
a greater number of items are classified under the highest taxonomy level than under the lowest taxonomy level;

determining, by the one or more processors, second taxonomy data closest to the first taxonomy data, wherein:
the second taxonomy data is associated with a group of items,
the first taxonomy data and the second taxonomy data have at least a common highest taxonomy level,
each of the first taxonomy data of the anchor item and the second taxonomy data includes at least three levels,
the determination that the second taxonomy data is closest to the first taxonomy data further comprises determining that at least the two highest levels of the first taxonomy data and the second taxonomy data are exactly the same, and
the first taxonomy data and the second taxonomy data have at least different lowest taxonomy levels;

determining, by the one or more processors, a most similar item to the anchor item from a group of items associated with the lowest level of the second taxonomy data, such that the first taxonomy data of the anchor item and the second taxonomy data of the most similar item have at least the two highest levels that are exactly the same and the lowest levels that are different, wherein the determining the most similar product from the group of products further comprises:
training a neural network using manually-created sets of similar products;
inputting product information of the anchor product and product information of each product of the group of products into the trained neural network;
performing, using a cosine similarity layer of the trained neural network, a comparison between the product information of the anchor product and the product information of each product of the group of products, the comparison comprising applying a cosine similarity function to at least one vector of the anchor product and at least one vector of each product of the group of products; and
determining, based on the comparison, that the product information of the anchor product is closest to product information of the most similar product; and

associating, by the one or more processors, the anchor item and the most similar item with one another in an item collection.