Abstract: A system 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, cause the one or more processors to perform: determining that a respective number of totes for a respective order of one or more orders can be reduced; reducing, using an infeasible totes loop, the respective number of the totes for the respective order to a respective reduced number of the totes; executing, as part of the infeasible totes loop, an item search; running the item search until a predefined number of iterations is reached; generating directions for a route of a pick walk based on a map of a retail facility; and facilitating displaying, on an electronic device, the route of the pick walk on the map of the retail facility. Other embodiments are disclosed herein.

Abstract: This application relates to systems and methods for automatically generating experiments based on experiment requests routed to micro-services (model sub-components) using a prefix-based routing mechanism. In some examples, experiment requests may parsed to determine lower layer services (e.g., components) whose properties need to be changed for a model iteration. Prefixes in requests may be used to route the experiment requests and portions thereof to appropriate services or layers for configuration at the micro-service level. Routing tables at each higher layer may be utilized to determine the correct sub-layers to redirect a request and/or portion thereof. At micro-service level, each micro-service may store and use a configuration table to match a received parameter in a request with a property and its corresponding value for the experiment.

Abstract: There are provided systems and methods relating to reconciling lottery transactions. In one form, the system includes point-of-sale (POS) systems at retail store for inputting of first lottery transaction data for lottery transactions occurring at the retail stores in which the lottery transactions correspond to lottery games being operated by a third party. It includes a POS server for extracting the first lottery transaction data and a retailer server for receiving second lottery transaction data from a server of the third party. Further, it includes a control circuit that conducts one-to-one matching of entries of the two data sets, determines whether a discrepancy exists based on the one-to-one matching, conducts one-to-many matching by iteratively aggregating different combinations of entries of one data set and comparing them with individual entries of the other data set, and determines whether a discrepancy exists based on the one-to-many matching.

Abstract: Systems and methods of fallback electronic communications are disclosed. A system is configured to receive a communication campaign including data identifying at least one communication channel and implement a fallback state machine having a first composite state corresponding to the at least one communication channel. An initial electronic communication is transmitted via the at least one communication channel and an initial timer having a first predetermined timeout period is implemented. When a confirmation is received prior to expiration of the initial timer, the fallback state machine transitions to a complete state. When the confirmation is not received prior to expiration of the initial timer, a first composite fallback state corresponding to a first set of fallback communication channels is implemented and a first fallback electronic communication is transmitted via the first set of fallback communication channels.

Abstract: This application relates to apparatus and methods for identifying fraudulent transactions. A computing device receives return data identifying the return of at least one item. The computing device obtains modified strategy data identifying at least one rule of a modified strategy. The rule may be based on the application of at least one dimensionality reduction algorithm to an initial strategy. The computing device applies the modified strategy to the received return data identifying the return of the at least one item, and determines whether the return of the at least one item is fraudulent based on the application of the modified strategy. The computing device generates fraud data identifying whether the return of the at least one item is fraudulent based on the determination, and may transmit the fraud data to another computing device to indicate whether the return is fraudulent.

Abstract: A computer-implemented method including automatically generating predictions of a respective number of items that a user is likely to reorder in each of groups of the items that a user has ordered historically. The method also can include ranking the groups based on the predictions of the respective number of the items the user is likely to reorder in each of the groups. The method additionally can include transmitting for display to the user a user interface including the groups of the items. Other embodiments are described.

Abstract: A transaction record is created showing a purchase transaction of a customer. A CV profile showing a list of items in the transaction obtained from images is also obtained. The items in the transaction record are compared to items on the list. When there is a discrepancy, an action to take is determined.

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 voice command from a user; transforming the voice command; transforming the voice command can include using a natural language understanding and rules execution engine into (a) an intent of the user to add recipe ingredients to a cart and (b) a recipe descriptor; determining a matching recipe from a set of ingested recipes based on the recipe descriptor; determining items and quantities associated with the items that correspond to a set of ingredients included in the matching recipe using a quantity inference algorithm; and automatically adding all of the items and the quantities associated with the items to the cart. Other embodiments are disclosed.

Abstract: This application relates to apparatus and methods for the monitoring of nodes within datacenters. In some examples, a computing device, such as a node, receives a monitoring file from a monitoring server, where the monitoring file includes a plurality of node health checks. The computing device is configured to execute the monitoring file based on a type of the computing device. Further, and based on the execution of the monitoring file, the computing device is configured to determine that at least one of the plurality of node health checks failed. In response to determining that the at least one of the plurality of node health checks failed, the computing device is configured to generate an alert message identifying the node health checks that failed. Further, the computing device is configured to transmit the alert message to the monitoring server for display.

Abstract: Systems, apparatuses, and methods are provided herein for monitoring beverage dispenser. A system for controlling beverage quality comprises a beverage dispenser monitoring unit comprising: a plurality of weight sensors each positioned below one of a plurality of syrup containers connected to a beverage dispenser, and a first network adapter configured to communicate with a control unit. The control unit configured to detect a low weight reading from a weight sensor of the plurality of weight sensors of the beverage dispenser monitoring unit via the second network adapter, determine a syrup container of the plurality of syrup containers associated with the weight sensor, and provide a notification of low syrup level indicating the syrup container to at least one of the plurality of user interface devices.

Abstract: A method including determining neighboring items from among sample items based on a respective embedding distance between a query image of a query item and a respective image of each of the neighboring items. The each of the sample items can comprise the respective image and at least one respective item label. The method further can include determining a respective normalized weight for each of the neighboring items based on the respective embedding distance between the query image and the respective image of the each of the neighboring items. The method also can include determining a query item label of the query item based on a weighted majority vote by the neighboring items via the respective normalized weight for the each of the neighboring items. Other embodiments are disclosed.

Abstract: A method for purchasing an item using a mobile device is provided. The method includes but is not limited to inputting identification information into the mobile device which identifies the item for purchase and generating an order for the item identified by the identification information. The method also includes but is not limited to displaying on a display of the mobile device an optical machine-readable representation of the order.

Abstract: A system 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 certain acts. The acts can include obtaining an original load design for loading a trailer to deliver stacks of pallets to physical stores. The load design specifies a respective floor spot assignment for each of the stacks. The original load design satisfies center-of-gravity constraints. The acts also can include generating fluid groups of the stacks to form an initial fluid grouping. The acts additionally can include determining that the fluid groups do not collectively satisfy the center-of-gravity constraints. The acts further can include until the fluid groups collectively satisfy the center-of-gravity constraints, repeatedly determining one or more infeasible groups from the fluid groups, and adjusting at least one of the one or more infeasible groups to update the fluid groups.

Abstract: This application relates to automatic processes that service data requests for information related to an item during varying temporal periods. For example, a computing device receives first attributes for an item, and generates a first surrogate key and a first super surrogate key based on the first attributes. Further, the computing device generates a first entry within a first table that includes the first surrogate key and the first super surrogate key. The computing device joins the first table to a second table based on natural keys. The computing device also receives second attributes for the item, and generates a second surrogate key for the item based on the second attributes. Further, the computing device generates a second entry within the first table that includes the second surrogate key and the first super surrogate key. The computing device also adjusts the first super surrogate key within the first entry.

Abstract: This application relates to apparatus and methods for natural language understanding in conversational systems using machine learning processes. In some examples, a computing device receives a request that identifies textual data. The computing device applies a natural language model to the textual data to generate first embeddings. In some examples, the natural language model is trained on retail data, such as item descriptions and chat session data. The computing device also applies a dependency based model to the textual data to generate second embeddings. Further, the computing device concatenates the first and second embeddings, and applies an intent and entity classifier to the concatenated embeddings to determine entities, and an intent, for the request. The computing device may generate a response to the request based on the determined intent and entities.

Abstract: Examples provides sale-restricted items management for self-checkout. A list of sale-restricted items is displayed via a graphical user interface (GUI) provided by a user interface. A notification component transmits a notification to a user device associated with an authorized user to verify a transaction responsive to an unauthorized user selection of a sale-restricted item from the list of sale-restricted items displayed. The notification includes an identification of the selected sale-restricted item and location of the selected sale-restricted item. A verification component authorizes completion of the transaction associated with the selected sale-restricted item by the unauthorized user on condition an age verification is obtained from the user device associated with the authorized user. Responsive to the authorization, an unlocking signal is sent to a locking storage device storing the selected sale-restricted item.

Abstract: A system 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, cause the one or more processors to perform operations: training, using labeled training data and a list of substitutes for an item, a machine learning algorithm; determining, using the machine learning algorithm, as trained, a respective similarity score for each substitute of the list of substitutes; ranking each substitute of the list of substitutes based on its respective similarity score; and re-training the machine learning algorithm based on at least the labeled training data and a highest ranked substitute of the list of substitutes. Other embodiments are disclosed herein.

Abstract: This application relates to apparatus and methods for applying trained machine learning models to determine an item's relevance to a search query. In some examples, a query and data identifying a plurality of items are received. Item attributes for each of the plurality of items are obtained, and features are generated based on the item attributes. Further, a score is generated for each item by applying a trained machine learning model to the corresponding features and the query. Matching attributes are determined for each of the plurality of items based on the corresponding item attributes and the query, and the score of each of the plurality of items is adjusted based on the matching attributes. Further, the ranking data is generated based on the adjusted score of each of the plurality of items. The ranking data may be transmitted to a web server for display of the items.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to detecting text in images. In some embodiments, a system for detecting text in images comprises a database configured to store images and a control circuit configured to retrieve an image, generate, based on the image, a collection of augmented images, detect characters in each of the augmented images, generate bounding boxes for the characters in each of augmented images, recognize the characters in each of the augmented images, select, based on the recognition of the characters in each of the augmented images, candidate characters, wherein the candidate characters are selected based on consistency of the recognition of the characters in each of the augmented images, detect, for the image, a color associated with the characters, and store, in the database, the image, the candidate characters, and the color associated with the characters.