Abstract: The disclosed computer-implemented method may include accessing updated data structures that are to be included in a user interface functionality test, where the updated data structures contribute to a user interface. The method may also include accessing live or snapshotted data captured from services running in a production environment, initiating generation of a first user interface instance using the updated data structures and using the accessed live or snapshotted data, and initiating generation of a second user interface instance using a different version of the data structures and using the same accessed live or snapshotted data. The method further includes comparing the first user interface instance to the second user interface instance to identify differences and then determine which outcome-defining effects the updated data structures had on the user interface based on the identified differences between the user interfaces.

Abstract: The disclosed computer-implemented method may include accessing updated data structures that are to be included in a user interface functionality test, where the updated data structures contribute to a user interface. The method may also include accessing live or snapshotted data captured from services running in a production environment, initiating generation of a first user interface instance using the updated data structures and using the accessed live or snapshotted data, and initiating generation of a second user interface instance using a different version of the data structures and using the same accessed live or snapshotted data. The method further includes comparing the first user interface instance to the second user interface instance to identify differences and then determine which outcome-defining effects the updated data structures had on the user interface based on the identified differences between the user interfaces.

Abstract: The disclosed computer-implemented method may include accessing updated data structures that are to be included in a user interface functionality test, where the updated data structures contribute to a user interface. The method may also include accessing live or snapshotted data captured from services running in a production environment, initiating generation of a first user interface instance using the updated data structures and using the accessed live or snapshotted data, and initiating generation of a second user interface instance using a different version of the data structures and using the same accessed live or snapshotted data. The method further includes comparing the first user interface instance to the second user interface instance to identify differences and then determine which outcome-defining effects the updated data structures had on the user interface based on the identified differences between the user interfaces.

Abstract: 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.

Abstract: The disclosed computer-implemented method may include accessing updated data structures that are to be included in a user interface functionality test, where the updated data structures contribute to a user interface. The method may also include accessing live or snapshotted data captured from services running in a production environment, initiating generation of a first user interface instance using the updated data structures and using the accessed live or snapshotted data, and initiating generation of a second user interface instance using a different version of the data structures and using the same accessed live or snapshotted data. The method further includes comparing the first user interface instance to the second user interface instance to identify differences and then determine which outcome-defining effects the updated data structures had on the user interface based on the identified differences between the user interfaces.

Abstract: 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 o

Abstract: 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.

Abstract: 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 o

Abstract: 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.

Abstract: 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.