Abstract:
Product data for a product is received by an attribute selection module. The product data includes product image data and product text data. This product data is used to generate a plurality of probability distributions for a category. The category includes a plurality of attributes, and the probability distribution includes a plurality of probabilities indicating the likelihoods that attributes of the category are applicable to the product. The plurality of probability distributions for the category are weighted and summed to generate a combined probability distribution for the category. An attribute label is determined by selecting an attribute from the category that is indicated to be most likely applicable to the product based on the combined probability distribution for the category. The attribute label is associated with the product. The attribute label enables other services to search for and retrieve the product based on the attribute.
Abstract:
Embodiments programmatically analyze each of a plurality of images in order to determine one or more visual characteristics about an item shown in each of the plurality of images. Data is stored corresponding to the one or more visual characteristics. An interface in is provided for which a user is able to specify one or more search criteria. In response to receiving the one or more search criteria, a search operation is performed to identify one or more items that have a visual characteristic that satisfies at least some of the one or more search criteria.
Abstract:
Embodiments programmatically analyze each of a plurality of images in order to determine one or more visual characteristics about an item shown in each of the plurality of images. Data is stored corresponding to the one or more visual characteristics. An interface in is provided for which a user is able to specify one or more search criteria. In response to receiving the one or more search criteria, a search operation is performed to identify one or more items that have a visual characteristic that satisfies at least some of the one or more search criteria.
Abstract:
Product data for a product is received by an attribute selection module. The product data includes product image data and product text data. This product data is used to generate a plurality of probability distributions for a category. The category includes a plurality of attributes, and the probability distribution includes a plurality of probabilities indicating the likelihoods that attributes of the category are applicable to the product. The plurality of probability distributions for the category are weighted and summed to generate a combined probability distribution for the category. An attribute label is determined by selecting an attribute from the category that is indicated to be most likely applicable to the product based on the combined probability distribution for the category. The attribute label is associated with the product. The attribute label enables other services to search for and retrieve the product based on the attribute.
Abstract:
Embodiments programmatically analyze each of a plurality of images in order to determine one or more visual characteristics about an item shown in each of the plurality of images. Data is stored corresponding to the one or more visual characteristics. An interface in is provided for which a user is able to specify one or more search criteria. In response to receiving the one or more search criteria, a search operation is performed to identify one or more items that have a visual characteristic that satisfies at least some of the one or more search criteria.