Walmart Apollo, LLC

Ajinkya More

Alessandro Magnani

Abon Chaudhuri

Shreyansh Prakash Gandhi

Abhinandan Krishnan

Bodhisattwa Prasad Majumder

Paolo Messina

Aditya Subramanian

Karthick Gopalswamy

Jayadeep Anil Shitole

A systems including one or more processors and one or more non-transitory computer readable media storing computing instructions that, when executed on the one or more processors, perform: receiving inventory information from two or more merchants; clustering the two or more merchants into a group of merchants; operating an optimization model for the subset of the inventory information for the group of merchants to determine a first inventory configuration for each of the two or more merchants at a seller location; operating the optimization model for the subset of the inventory information the group of merchants to determine a second inventory configuration for each of the two or more merchants at the seller location; and combining the first inventory configuration and the second inventory configuration to determine third inventory configuration for each of the two or more merchants at the seller location. Other embodiments are described.

Systems and methods for supply chain management

A product image evaluation system. In embodiments, the system comprises or interacts with a product database comprising a product information record that comprises a product identifier and a product category for a product, and an image database comprising a plurality of candidate images for the product. In embodiments the image database can comprise images received from a plurality of different sources. The system can comprise a parameterized grouping engine configured to separate images into groups of similar images, an image selector configured to select one or more images from each group, and an image sorter configured to determine an order of the selected images. Embodiments can distill the superset of all available images to provide a set of images that are 'sufficiently different' from each other and satisfy quality requirements. As a result, no images containing unique information are left behind, and images containing duplicate or irrelevant information are discarded.

Product image evaluation system and method

Systems and methods including 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 retrieving a first product offer from a first seller for a first product to offer for sale on a website of an online retailer, determining if the first product offer for the first product matches one or more existing candidate product offers in a catalog of the online retailer using one or more sets of rules, and, if the first product offer matches the one or more existing candidate product offers, coordinating displaying at least a portion of the first product offer on the website of the online retailer.

Systems and methods for matching products in the absence of unique identifiers

Some embodiments can comprise a system comprising one or more computer processing modules and one or more non-transitory storage modules storing computing instructions configured to run on the one or more computer processing modules a perform acts of: receiving, at the one or more computer processing modules and from a third-party electronic device, a title for a product; dividing, at the one or more computer processing modules, the title into a sequence of tokens; storing, by the one or more computer processing modules onto the one or more non-transitory storage modules, the sequence of tokens; determining, at the one or more computer processing modules and using a sequence labeling model, a type of each token of the sequence of tokens; storing, by the one or more computer processing modules onto the one or more non-transitory storage modules, the type of each token of the sequence of tokens; encoding, at the one or more computer processing modules, each token of the sequence of tokens to indicate the type of each token of the sequence of tokens, wherein the type of each token of the sequence of tokens can comprise a BIO encoding scheme, wherein: a label B of the BIO encoding scheme can indicate a first token of a brand name; a label I of the BIO encoding scheme can indicate a subsequent token of the brand name; and a label O of the BIO encoding scheme can indicate a token that is not part of the brand name; determining, at the one or more computer processing modules, a brand name present in the title using each token of the sequence of tokens, as encoded; storing, by the one or more computer processing modules onto the one or more non-transitory storage modules, the brand name present in the title; normalizing, at the one or more computer processing modules, the brand name present in the title to create a standardized representation of the brand name; writing, by the one or more computer processing modules onto the one or more non-transitory storage modules, the standardized representation of the brand name present in the title to an empty database entry associated with the product; and in response to a search request from a user, transmitting instructions to a user display to display a representation of the standardized representation of the brand name for each token of the sequence of tokens. Other embodiments are also disclosed herein.

Method and system for attribute extraction from product titles using sequence labeling algorithms

A system and method for attribute extraction from product titles is presented. A set of product titles are read by an embodiment. The product titles are separated into a sequence of tokens, the tokens being determined by the presence of a separator character. The sequences of tokens are labeled according to a specific encoding scheme to denote attributes of a title, such as brand name and other features. The characteristics of the attributes within the title are determined to build a sequence labeling algorithm. The results of the encoding is compared to a normalization dictionary comparing standardized attributes. A blacklist can be consulted to further refine the method. A further validation can be performed to catch any remaining mistakes. Thereafter, a database entry can be made to associate the attribute with the item. A training set can be used to initialize the learning model. Other embodiments are also disclosed herein.

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Sunnyvale, CA, United States of America

Ajinkya More