Abstract: 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 receiving attribute data comprising a set of unstructured attribute data and a set of structured attribute data, analyzing the set of unstructured attribute data by processing through a first set of one or more Long Short Term Memory (LSTM) layers, to obtain an unstructured semantic signature, analyzing the set of the structured attribute data by processing through a first set of one or more Convolutional Neural Network (CNN) layers, to obtain a structured semantic signature, analyzing the unstructured semantic signature and the structured semantic signature, and classifying the item in one or more item categories. Other embodiments are disclosed herein.

Abstract: A system can include one or more processors and non-transitory computer-readable media storing computing instructions configured to run on the one or more processors to cause the one or more processors to perform: extracting one or more visual attributes of a requested product in a domain based on an image describing the requested product in an inquiry from a user; extracting one or more textual attributes of the requested product based on a text describing the requested product in the inquiry; determining projected requested products, in a product graph relating to the domain and dynamically generated by machine learning, based on the one or more visual attributes of the requested product and the one or more textual attributes of the requested product; determining one or more substitutes for the requested product based on scores of candidate products in the product graph, wherein: a greater weight is given to visual distances than textual distances in determining the scores; the visual distances and the text

Abstract: A system can include one or more processors and non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform a method for determining one or more substitutes for a product requested in an inquiry from a user. The method comprises one or more of the steps including receiving an inquiry from a user, which comprises a requested product; extracting one or more attributes of the requested product based on the inquiry; determining a context of the inquiry; and determining one or more substitutes for the requested product from an inventory database based on a distance between the requested product and each substitute of the one or more substitutes, as projected in a product graph relating to a domain of the requested product and the context of the inquiry.

Abstract: A system can include one or more processors and non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform a method for determining one or more substitutes for a product requested in an inquiry from a user and the order of the one or more substitutes to be transmitted to the user.

Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of receiving a digital image comprising multiple items; determining an embedding for the digital image using a machine learning algorithm trained on one or more combined digital images, the combined digital image comprising one or more annotated digital images; identifying an item of the multiple items in the digital image; and facilitating an alteration of a GUI on an electronic device in response to identifying the item in the digital image.

Abstract: A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform receiving a title of an item associated with an online catalog; interpreting, using a natural language model, one or more attributes of the predetermined set of attributes; determining a first title quality score for the title based on a first rule; determining a second title quality score for the title based on a second rule; determining an aggregated title quality score for the title based on at least the first title quality score and the second title quality score; generating a content quality list for the title; and sending instructions to display, on a user interface of an electronic device, a content quality dashboard comprising the content quality list for the title of the item. Other embodiments are disclosed.

Abstract: An advertising system is provided and generally includes a computing device that can receive attribute data from a plurality of information sources for an item. The computing device can determine a first number of sources for which the same attribute value for an attribute of the item is received, and can determine a second number of sources for which any attribute value for the same attribute of the item is received. The computing device can generate an attribute confidence value for the attribute based on the first number of sources and the second number of sources, indicating how likely the attribute value for the attribute is correct. The computing device can determine an item confidence value for the item based on multiple attribute confidence values for the item. Based on the item confidence value, the computing device may provide an attribute error signal indicating an attribute value error.

Abstract: A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform receiving a title of an item associated with an online catalog; interpreting, using a natural language model, one or more attributes of the predetermined set of attributes; determining a first title quality score for the title based on a first rule; determining a second title quality score for the title based on a second rule; determining an aggregated title quality score for the title based on at least the first title quality score and the second title quality score; generating a content quality list for the title; and sending instructions to display, on a user interface of an electronic device, a content quality dashboard comprising the content quality list for the title of the item. Other embodiments are disclosed.

Abstract: A method including building a relevancy model based on items in an item catalog. The method also can include building a title interpreter model based on titles of the items in the item catalog. The method additionally can include retrieving target attribute values that are associated with a target attribute name of a target item in the item catalog. The target attribute values can be received from multiple sources. The method further can include generating a respective relevancy score for each one of the target attribute values using the relevancy model. The method additionally can include generating a respective precision score for the each one of the target attribute values based on the title interpreter model. The method further can include determining a respective weight for the each one of the target attribute values based on the respective relevancy score for the each one of the target attribute values and the respective precision score for the each one of the target attribute values.

Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of receiving one or more digital images from a repository of digital images; annotating the one or more digital images from the repository of digital images; digitally altering the one or more digital images, as annotated, from the repository of digital images; digitally combining the one or more digital images, as annotated and digitally altered, with at least one or more portions of one or more other digital images of the repository of digital images to create one or more combined digital images; training a machine learning algorithm on the one or more combined digital images; and storing the machine learning algorithm, as trained, in the one or more non-transitory computer readable storage devices.

Abstract: An advertising system is provided and generally includes a computing device that can receive attribute data from a plurality of information sources for an item. The computing device can determine a first number of sources for which the same attribute value for an attribute of the item is received, and can determine a second number of sources for which any attribute value for the same attribute of the item is received. The computing device can generate an attribute confidence value for the attribute based on the first number of sources and the second number of sources, indicating how likely the attribute value for the attribute is correct. The computing device can determine an item confidence value for the item based on multiple attribute confidence values for the item. Based on the item confidence value, the computing device may provide an attribute error signal indicating an attribute value error.

Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform: for each respective item of one or more items: identifying one or more respective item attributes in an existing title for the respective item; and determining at least one respective item attribute of the one or more respective item attributes to include in an alternative title for the respective item based on an attribute importance score for each respective item attribute of one or more item attributes of the respective item; generating at least one first modified title for at least one first item of the one or more items, the at least one first modified title comprising at least one first item attribute of the at least one first item; and coordinating displaying of the at least one first modified title for the at least one first item on a website. Other embodiments are disclosed herein.

Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of receiving a digital image comprising multiple items; determining an embedding for the digital image using a machine learning algorithm trained on one or more combined digital images, the combined digital image comprising one or more annotated digital images; identifying an item of the multiple items in the digital image; and facilitating an alteration of a GUI on an electronic device in response to identifying the item in the digital image.

Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of receiving one or more digital images from a repository of digital images; annotating the one or more digital images from the repository of digital images; digitally altering the one or more digital images, as annotated, from the repository of digital images; digitally combining the one or more digital images, as annotated and digitally altered, with at least one or more portions of one or more other digital images of the repository of digital images to create one or more combined digital images; training a machine learning algorithm on the one or more combined digital images; and storing the machine learning algorithm, as trained, in the one or more non-transitory computer readable storage devices.

Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform: for each respective item of one or more items: identifying one or more respective item attributes in an existing title for the respective item; and determining at least one respective item attribute of the one or more respective item attributes to include in an alternative title for the respective item based on an attribute importance score for each respective item attribute of one or more item attributes of the respective item; generating at least one first modified title for at least one first item of the one or more items, the at least one first modified title comprising at least one first item attribute of the at least one first item; and coordinating displaying of the at least one first modified title for the at least one first item on a website. Other embodiments are disclosed herein.

Abstract: 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 receiving an external catalog comprising external attributes for each product of a plurality of products, mapping the external attributes from the external catalog to internal attributes for each product of the plurality of products in an internal catalog for an online retailer using an ensemble learning technique comprising a plurality of algorithms, incorporating the external attributes of the external catalog into the internal attributes in the internal catalog as mapped, and coordinating displaying of the external attributes and the internal attributes on a website of the online retailer.

Abstract: A system can include one or more processors and non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform a method for determining one or more substitutes for a product requested in an inquiry from a user. The method comprises one or more of the steps including receiving an inquiry from a user, which comprises a requested product; extracting one or more attributes of the requested product based on the inquiry; determining a context of the inquiry; and determining one or more substitutes for the requested product from an inventory database based on a distance between the requested product and each substitute of the one or more substitutes, as projected in a product graph relating to a domain of the requested product and the context of the inquiry.

Abstract: A system can include one or more processors and non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform a method for determining one or more substitutes for a product requested in an inquiry from a user and the order of the one or more substitutes to be transmitted to the user.

Abstract: 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 receiving attribute data comprising a set of unstructured attribute data and a set of structured attribute data, analyzing the set of unstructured attribute data by processing through a first set of one or more Long Short Term Memory (LSTM) layers, to obtain an unstructured semantic signature, analyzing the set of the structured attribute data by processing through a first set of one or more Convolutional Neural Network (CNN) layers, to obtain a structured semantic signature, analyzing the unstructured semantic signature and the structured semantic signature, and classifying the item in one or more item categories. Other embodiments are disclosed herein.

Abstract: 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 identifying one or more product attributes in an existing title for a product, determining at least one product attribute to include in an alternative title for the product, determining that the at least one product attribute in the alternative title for at least a the product does not correspond to the one or more product attributes in the existing title for the product, automatically inserting the at least one product attribute in the alternative title for the product into a modified title for the product, and coordinating displaying of the modified title for the product on a website associated with the online retailer.