Abstract: A computer-implemented method comprises receiving, from a computing device associated with a merchant, product information about a product; classifying, based on the product information, the product into a handling class associated with handling of the product; and storing an indication of classification in association with the product information about the product.

Abstract: An image processing method and system that generates output images. The system receives a first input image depicting a first set of products and determines the first set of products and corresponding first product categories. The system then receives, on a user interface of a requestor device, a second input image depicting other products selected as being of interest having corresponding second product categories for the other products. In response to a match between one of the first product categories and the second product categories: the system applies the first input image and the second input image to generative adversarial networks (GANs). Each GAN is trained using image dataset for corresponding ones of the first and second product categories, to generate an output image replacing at least a portion of first input image with the second input image, the replacement based on the match between the product categories.

Abstract: Generative language models are able to generate a sequence of text that may closely mimic a native human speaker's own generated text. However, technical challenges exist when implementing a generative language model for generating product descriptions. The model may output certain inaccuracies due to the predictive nature of generating the output. Further, the model does not have the ability to identify words from the product description that a merchant may want to modify, nor the ability to provide meaningful alternatives to such words. In some embodiments, a natural language processor might be built and/or trained using classification data. The natural language processor may identify one or more words and/or phrases in a product description as a candidate for modification. The product description might then be displayed on a merchant-facing user interface with an indication that the candidate for modification may be modified.

Abstract: When a user is interacting with web content of an online store/marketplace, it may be desirable for the web content to display information related to the delivery time of the product. Determining the delivery time information in real-time may be complex and unreliable due to the number of factors incorporated into the computation and because one or more of the factors might not be known or inferable until immediately before generation of the delivery time information. In some embodiments, the delivery timeline may be partitioned into non-overlapping segments, and segment data structures may be configured for each segment. In some embodiments, a master data structure is generated based on the segment data structures that includes the probability of different delivery times for given combinations of input data. In some embodiments, the web content may include delivery time information based on the probabilities in the master data structure.

Abstract: A computer-implemented method comprises receiving, from a computing device associated with a merchant, product information about a product; classifying, based on the product information, the product into a handling class associated with handling of the product; and storing an indication of classification in association with the product information about the product.