Abstract: Methods, systems, and computer-readable storage media for processing images captured in a retail store and automatically identifying a product shortage are provided. In one implementation, a system may access information describing a desired placement of products on at least one store shelf. The system may analyze a first image captured at a first time to determine that a first quantity of products exceeds a quantity threshold. The system may analyze a second image captured at a second time later than the first time to determine that a second quantity of products is below the quantity threshold. The system may avoid initiating an unscheduled action to cause restocking until a third time later than the second time. Based on a determination that a third quantity of products at the third time are below the quantity threshold, the system may provide information indicative of a product shortage.

Abstract: The present disclosure relates to systems and methods for identifying products and monitoring planogram compliance using analysis of image data. In one implementation, the method may include accessing at least one planogram describing a desired placement of a plurality of product types on shelves of a plurality of retail stores; receiving image data from the plurality of retail stores; analyzing the image data to determine an actual placement of the plurality of product types on the shelves of the plurality of retail stores; determining at least one characteristic of planogram compliance based on detected differences between the at least one planogram and the actual placement of the plurality of product types on the shelves of the plurality of retail stores; and receiving checkout data from the plurality of retail stores reflecting sales of at least one product type from the plurality of product types.

Abstract: A system for reducing product shortage durations in retail stores based on analysis of image data is provided. The system may comprise: a communication interface configured to receive image data from retail stores indicative of a product shortage of a product type relative to information describing a placement of products of a product type on a store shelf; and at least one processor configured to: analyze the image data to detect occurrences of product shortages of the product type in the retail stores and determine durations associated with the occurrences; identify a common factor contributing to the duration of part of the occurrences of the product shortages; determine an action, associated with the at least one common factor, for potentially reducing product shortage durations of future shortages of the product type in the retail stores; and provide information associated with the identified action to an entity.

Abstract: The present disclosure relates to systems and methods for identifying products and monitoring planogram compliance using analysis of image data. In one implementation, the method may include accessing at least one planogram describing a desired placement of a plurality of product types on shelves of a plurality of retail stores; receiving image data from the plurality of retail stores; analyzing the image data to determine an actual placement of the plurality of product types on the shelves of the plurality of retail stores; determining at least one characteristic of planogram compliance based on detected differences between the at least one planogram and the actual placement of the plurality of product types on the shelves of the plurality of retail stores; and receiving checkout data from the plurality of retail stores reflecting sales of at least one product type from the plurality of product types.

Abstract: A search engine responding to a user query to find relevant data assets in a federation business data lake (FBDL) system by monitoring and recording all of the interactions of users interacting with data assets in the FBDL system, providing all of the user interactions to a recommendation engine, calculating relevance of information in the FBDL system to each user, and recommending one or more new data assets to a target user based on the relevance of the information. The relevance comprises the target user's past interactions with the data assets based and the cumulative interactions of other users with the data assets, such that if one or more of the other users has similar interaction behavior to the target user, then knowledge of the one or more other users can impact the relevance of the information with regard to the one or more new data assets suggested to the target user.

Abstract: A system for automatically addressing detected conditions within the retail store is provided. The system may include at least one processor configured to receive a plurality of images depicting a plurality of products displayed on a plurality of store shelves; retrieve reference data specifying a desired state of the retail store; use the reference data to detect an indicator of a first service-improvement condition; use the reference data to detect an indicator of a second service-improvement; determine a first product-related task for addressing the first service-improvement condition; determine a second product-related task for addressing the second service-improvement condition; access a database storing information indicative of a first employee and a second employee on duty during a time interval over which the plurality of images was received; and assign the first product-related task to the first employee and assign the second product-related task to the second employee.

Abstract: A system for processing images captured in a retail store and automatically generating low-stock alerts includes at least one processor configured to: receive image data associated with images captured during a first period of time by one or more image capturing devices mounted in the retail store; analyze the image data to identify a restocking event, at least one facing event, and a low-stock event; determine a demand pattern for products from the specific product type based on the identified restocking event, the at least one facing event, and the low-stock event; receive additional image data associated with images captured during a second period of time, subsequent to the low-stock event; based on the additional image data and the determined demand pattern, predict when a next low-stock event will occur; and generate an alert associated with the predicted next low-stock event.

Abstract: A system for acquiring images of products in a retail store is disclosed. The system may include at least one first housing configured for location on a retail shelving unit, and at least one image capture device included in the at least one first housing and configured relative to the at least one first housing such that an optical axis of the at least one image capture device is directed toward an opposing retail shelving unit when the at least one first housing is fixedly mounted on the retail shelving unit. The system may further include a second housing configured for location on the retail shelving unit separate from the at least one first housing, the second housing may contain at least one processor configured to control the at least one image capture device and also to control a network interface for communicating with a remote server.

Abstract: A system for identifying products and tracking inventory in a retail store based on analysis of image data is provided. The system may comprise at least one processor configured to receive image data from a plurality of image sensors mounted in a retail store; analyze the image data to estimate a current inventory of at least one product type in the retail store; receive product supply information associated with the at least one product type in the retail store; determine that an online order from a virtual store made during a first time period will be fulfilled by an employee of the retail store during a second time period; determine a predicted inventory of the at least one product type during the second time period; and provide information to the virtual store regarding the predicted inventory of the at least one product type during the second time period.

Abstract: A system for reducing product shortage durations in retail stores based on analysis of image data is provided. The system may comprise: a communication interface configured to receive image data from retail stores indicative of a product shortage of a product type relative to information describing a placement of products of a product type on a store shelf; and at least one processor configured to: analyze the image data to detect occurrences of product shortages of the product type in the retail stores and determine durations associated with the occurrences; identify a common factor contributing to the duration of part of the occurrences of the product shortages; determine an action, associated with the at least one common factor, for potentially reducing product shortage durations of future shortages of the product type in the retail stores; and provide information associated with the identified action to an entity.

Abstract: A system for processing images captured in a retail store and automatically identifying a product shortage is provided. The system may comprise at least one processor configured to: access information describing a placement of products; receive image data from an image sensor; analyze a first image captured at a first time to determine that a first quantity of products exceeds a quantity threshold; analyze a second image captured at a second time to determine that a second quantity is below the quantity threshold; based on the determination that the first quantity exceeds the quantity threshold, avoid initiating an unscheduled action to cause restocking the store shelf with products until a third time; analyze a third image captured at the third time to determine that a third quantity is below the quantity threshold; and based on the determination, provide information indicative of a product shortage at the store shelf.

Abstract: A system for identifying products and tracking inventory in a retail store based on analysis of image data is provided. The system may comprise at least one processor configured to receive image data from a plurality of image sensors mounted in a retail store; analyze the image data to estimate a current inventory of at least one product type in the retail store; receive product supply information associated with the at least one product type in the retail store; determine that an online order from a virtual store made during a first time period will be fulfilled by an employee of the retail store during a second time period; determine a predicted inventory of the at least one product type during the second time period; and provide information to the virtual store regarding the predicted inventory of the at least one product type during the second time period.

Abstract: The present disclosure relates to systems and methods for identifying products and monitoring planogram compliance using analysis of image data. In one implementation, the method may include accessing at least one planogram describing a desired placement of a plurality of product types on shelves of a plurality of retail stores; receiving image data from the plurality of retail stores; analyzing the image data to determine an actual placement of the plurality of product types on the shelves of the plurality of retail stores; determining at least one characteristic of planogram compliance based on detected differences between the at least one planogram and the actual placement of the plurality of product types on the shelves of the plurality of retail stores; and receiving checkout data from the plurality of retail stores reflecting sales of at least one product type from the plurality of product types.

Abstract: The present disclosure relates to systems and for identifying products and tracking inventory in a retail store based on analysis of image data. In one implementation, the system may include processor configured to receive image data from a plurality of image sensors mounted in a retail store; analyze the image data to estimate a current inventory of at least one product type in the retail store; receive product supply information associated with the at least one product type in the retail store; determine that an online order from a virtual store made during a first time period will be fulfilled by an employee of the retail store during a second time period; and determine, based on the current inventory estimated by analyzing the image data and the product supply information, a predicted inventory of the at least one product type during the second time period.

Abstract: The present disclosure relates to systems and methods for processing images captured in a retail store and automatically addressing detected conditions within the retail store. In one implementation, the system may include a processor configured to receive a plurality of images depicting a plurality of products displayed on a plurality of store shelves; detect in the plurality of images an indicator of a first service-improvement condition relating to the plurality of products; detect in the plurality of images an indicator of a second service-improvement condition relating to the plurality of products; determine a first product-related task for addressing the first service-improvement condition; determine a second product-related task for addressing the second service-improvement condition; and access a database storing information indicative of a first employee and a second employee on duty during a time interval over which the plurality of images was received.

Abstract: A System, Computer Program Product, and Computer-executable method for testing a production system, the System, Computer Program Product, and Computer-executable method including receiving information related to the production system, receiving production data from the production system, creating a virtual production system based off the production system using the received information and the received production data, and analyzing the production system by performing tests on the virtual production system.

Abstract: An apparatus comprises a processing platform configured to implement a cluster labeling system for documents comprising unstructured text data. The cluster labeling system comprises a clustering module and a visualization module. The clustering module implements a topic model generator and is configured to assign each of the documents to one or more of a plurality of clusters based at least in part on one or more topics identified from the unstructured text data using at least one topic model provided by the topic model generator. The visualization module comprises multiple view generators configured to generate respective distinct visualizations of a selected one of the clusters. The multiple view generators include at least a bigram view generator configured to provide a visualization of a plurality of term pairs from the selected cluster, and a summarization view generator configured to provide a visualization of representative term sequences from the selected cluster.

Abstract: An apparatus comprises a processing platform configured to implement an automated content inference system for unstructured text data. The automated content inference system comprises a data indexer, a dictionary generator, a topic model generator, and a visualization generator. The data indexer is configured to process the unstructured text data to construct a term index for a given document. The dictionary generator is configured to process the term index to construct an in-domain dictionary. The topic model generator is configured to process the in-domain dictionary to construct a topic model. The visualization generator is configured to provide an output display showing assignment of one or more topics to the given document based on the topic model. The unstructured text data illustratively comprises unstructured service request summaries from a service events database.