Abstract: A method including training a recurrent neural network model to create a trained model based at least in part on: (a) first images associated with first items on a website, (b) first search terms used by users of the website to search for the first items on the website, and (c) personal features of the users. The method also can include receiving an input image that was uploaded by a current user. The method additionally can include obtaining a user encoded representation vector for the current user based on a set of personal features of the current user. The method further can include generating an image encoded representation vector for the input image. The method additionally can include deriving search terms that are personalized to the current user for the one or more items depicted in the input image, using the trained model and based on the user encoded representation vector for the current user and the image encoded representation vector for the input image. Other embodiments are disclosed.

Abstract: Systems and methods for improved Spoken Language Understanding (“SLU”) are provided. The methods may comprise receiving an utterance from a user, contextualizing a plurality of words in the utterance, providing the contextualized words to the slot detector to determine the probability of a word forming the beginning or end of a slot to determine slots and nested slots, an intent classifier to determine the probability of a word conveying a user intent, and a slot classifier that applies specific labels to each slot and nest slot. The SLU method may employ a model and jointly trains the model for each task (determining beginning and end of slots, intents, and slot classifications) using a combined loss function.

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; identifying a foreground of the one or more digital images; analyzing the foreground of the one or more digital images to identify a skin region in the foreground of the one or more digital images; when the skin region is identified, clustering a non-skin remainder of the foreground of the one or more digital images into one or more clusters; extracting one or more patches of the one or more digital images from the one or more clusters of the foreground of the one or more digital images; determining one or more scores for the one or more patches of the one or more digital images; and coordinating displaying a patch of the one or more patches on an electronic display based on the one or more scores for the one or more patches. 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: receiving, from one or more electronic devices of one or more users, one or more orders for pickup at a location during a first window of time; at a first time during the first window of time, determining when a designated pickup area at the location exceeds a predetermined level of congestion using: (1) continuously received mobile check-ins at the location; and (2) congestion data of the designated pickup area at the location; and when the designated pickup area at the location does not exceed the predetermined level of congestion during the first window of time, as determined at the first time, causing a pickup electronic device of a pickup to display a pickup request at the location to fulfill at least one order of the one or more orders during the first window of time. Other embodiments are disclosed herein.

Abstract: Systems and methods for generating and implementing reusable interface components is disclosed. A schema is loaded from a repository. The schema defines one or more containers configured to receive a component therein. At least one component is selected for insertion into a first container defined by the schema. The at least one component includes a frontend portion and a backend portion. The fronted portion defines at least one customization of the component. The at least one customization of the at least one component is defined and the at least one component is implemented using a predetermined decoding process.

Abstract: Systems and methods for facilitating computer-vision-based detection and identification of consumer products comprise a support surface for supporting thereon one or more consumer products to be detected and a plurality of digital cameras each arranged at a different height relative to the support surface and positioned such that a field of view of each of the digital cameras includes the consumer product(s) located on the support surface. Movement of the support surface and/or the digital cameras permits the digital cameras to capture images of the consumer product from different angles of view and up to a full 360 degree of rotation around the at least one consumer product. A computing device uses at least the image data from such images to train a computer vision consumer product identification model to generate a reference image data model to be used for recognition of the at least one consumer product.

Abstract: This application relates to systems and methods for automatically generating fraud strategies. A system may comprise customer computing devices, a database, and retailer computing device(s). The retailer computing device(s) are configured to receive data related to customer transactions, calculate a negative reaction score, negative resolution score, anomaly score, and impact score for at least one value of the received data, determine whether the calculated scores are greater than or equal to respective thresholds, identify a value of the received data as a potentially fraudulent data value when one or more of the calculated scores is greater than or equal to its respective threshold, generate an output comprising a list of potentially fraudulent data value(s) and impact scores, identify area(s) of high impact leaks based on the output, and determine which customer computing devices are executing fraudulent transactions based on the identification of areas of high impact leaks.

Abstract: In some examples, a system may include a first computing device communicatively coupled to a second computing device. Additionally, the first computing device is configured to obtain, from the second computing device, check-in data indicating an arrival of the user of the second computing device at a first location, and in response to obtaining the check-in data, determine current wait times. Moreover, the first computing device is configured to determine a first number of customers waiting for service, determine a first number of associates available to assist the first number of customers, and determine an expected wait time for the user operating the second computing device based at least on the current wait times. In some examples, the first number of customers waiting for service, and the first number of associates available. Further, the first computing device is configured to transmit the expected wait time to the second computing device.

Abstract: A disclosed system for transport asset monitoring, for example monitoring truck trailer unloading progress at large retail locations, includes an artificial intelligence (AI) solution for managing operations at a facility. The AI solution analyzes current load percentage and other data to predict availability for moving the transport asset and ability to accept a new incoming transport asset. Predictions of availability can reduce response times, resulting in higher utilization rates for assets, thereby improving efficiency. An exemplary system includes a sensor configured to sense operation progress parameter data for a transport asset; and logic to receive the operation progress parameter data from the sensor; determine, using the AI solution and based at least on the operation progress parameter data, a predicted milestone parameter; and report the predicted milestone parameter to a remote node.

Abstract: This application relates to apparatus and methods for determining data outputs to advertise on a platform such as a website. A computing device receives a website search request and determines a search term keyword. The computing device also determines a plurality of item accounts, such as sponsor campaigns, based on the search term keyword and a corresponding keyword of each item account. Each item account also includes a corresponding data output, such as a digital advertisement. The computing device identifies one of the item accounts based on determining an engagement probability for the digital advertisement of each item account. The engagement probability is determined based on aggregated impression and engagement data for the digital advertisement. The computing device provides the digital advertisement for the identified item account to a server, which may display the digital advertisement on the platform.

Abstract: This application relates to systems and methods for facilitating online search based on offline transaction data.

Abstract: A categorization system can include a computing device that is configured to obtain a plurality of data items over a threshold analysis period from an incoming data database in response to a threshold analysis interval elapsing. The computing device can also be configured to select a categorization model from a model database. The computing device can also be configured to, for each data item of the plurality of data items, apply the categorization model to the data item to identify at least one topic associated with the corresponding data item. The computing device can also be configured to generate a categorization visualization indicating a frequency of data items corresponding to each topic. The computing device can also be configured to transmit the categorization visualization to at least one of: (i) a user interface of an analyst device and (ii) a categorized database.

Abstract: Systems and methods are disclosed for a voice/chatbot building system. The voice/chatbot builder may involve receiving an identified intent, receiving a task related to the identified intent, and receiving a response related to both the identified intent and the task. The identified intent, task, and response may form a first conversation. The first conversation may be linked to other conversations to establish contextual relationships among conversations and determine conversation priority. Voice/chatbot building may also train natural language processing machine learning algorithms.

Abstract: Systems and methods are provided herein for producing and vending ice in an energy-efficient manner. A system for producing and vending ice comprises: an ice-making device configured to manufacture ice; a reservoir coupled to the ice-making device and configured to store the manufactured ice manufactured; and a control circuit communicatively coupled to the ice-making device, the control circuit configured to: determine a beginning ice inventory at a first time; determine a predicted ice demand for a first period, wherein the predicted ice demand is a function of at least a historical factor, a weather factor, a customer social event factor, and a public social event factor; determine an ice manufacturing quantity based on the beginning ice inventory, the predicted ice demand, and a manufacturing capacity of the ice-making device; and cause the ice-making device to produce an amount of ice consistent with the determined ice manufacturing quantity.

Abstract: Approaches are provided that determine and fine-tune product assortments carried by retail stores. In aspects, the number of stores that carry the item, the sales performance of the item, the loyalty of customers to the item, whether substitutes for the item can be found, and other factors are used to determine an actions such as increasing or decreasing the shelf space for an item.

Abstract: Horizontally-scalable systems and methods for scheduling and optimizing deliveries are described herein. At least one scheduler is configured to receive a request to schedule a delivery for an origination location. The request includes a desired time slot. The request is compared to a persistent delivery snapshot for the origination location to determine availability of the desired time slot. An interim delivery snapshot including the requested delivery is generated when the persistent delivery snapshot has an available time slot corresponding to the desired time slot. At least one optimizer is configured to receive the interim delivery snapshot and generate an updated persistent delivery snapshot by applying an optimization process to the interim delivery snapshot.

Abstract: An electronic shelf label (ESL) system is discussed. An ESL affixed to a shelf facing assists stock associates in managing products on the shelf. More particularly, the ESL may receive and display step-by-step instructions and/or graphical depictions on a display screen of the ESL that are received from a computing device-executed optimization module. The instructions may be generated to minimize the number of required actions by the stock associate and guide the associate in arranging products on the shelf. The displayed instructions may be determined based on a planogram. The planogram may be generated from a range of criteria including historical profit and loss data, inventory data, supply and demand data and/or labor cost data.