Abstract: Systems and methods for recommending a size of disposable article to be worn by a subject are provided. An image of the subject is analyzed to determine the subject's fit parameters. The fit parameters are applied to sizing models of various disposable articles.

Abstract: A third-party negotiation automation tool for generating cost estimates on behalf of a seller is described herein. In response to receiving a request for a product from a buyer, a seller may choose to participate in a negotiation for fulfilling the request. The system may utilize one or more data sources, such as user-provided data, third-party data, and the like, to generate a cost estimate on behalf of the seller for fulfilling the request. The seller may choose to accept, modify, or decline the generated cost estimate before providing the cost estimate to the buyer for acceptance. This process may continue for one or more rounds, dependent upon the request, with the final cost estimates provided to the buyer for selection at the conclusion of the one or more rounds.

Abstract: Systems and methods for facilitating a purchase are described. A user logs in to a payment service provider site. The user provides authorization to use a one-page checkout service. The user's information is captured during the session, and a cookie is placed on the user's device. When the user goes on a merchant website and checks out using the payment service provider, the payment service provider detects the cookie on the user device. The payment service provider uses the cookie, and in one embodiment, centrally stored information, to populate the one-page checkout page with the last used payment. In various embodiments, the one-page checkout page also displays a shipping address.

Abstract: When a person visits a physical retail store, the merchant often does not have enough information about the person to make meaningful product recommendations. Also, a physical retail store typically has products physically distributed throughout the store. It may be desirable to have some sort of relationship between where the customer is and the location of the product being recommended. In some embodiments, when a person visits the store, a computer determines an identity of the person and generates a product recommendation based on user-specific information for that person. In some embodiments, generating the product recommendation includes detecting that a field of view of a camera of the device has changed, and in response determining a plurality of products within or proximate to a current field of view of the camera. At least one of the plurality of products is then identified as the recommended product.

Abstract: Systems, methods, and computer-readable media are disclosed for processing input data to determine an entity such as a product, service, user profile, etc. referenced in or otherwise relevant to a semantic context of the input data. Information related to the entity may be provided as an information package (e.g., a card) that is shareable as part of an electronic message. The card may include a representation of a network resource identifier that identifies a network resource, a network location of the network resource, and an access mechanism for accessing a representation (e.g. a product detail page) of the network resource. The network resource identifier may include one or more tags or tokens that identify an electronic messaging application provider and/or a user such as a sender or recipient of an electronic message that includes the card so as to enable compensating the provider and/or the user for a purchase of a product or service to which the card relates.

Abstract: This disclosure describes systems and techniques for identifying events that occur within an environment using image data captured at the environment. For example, one or more cameras may generate image data representative of a user interacting with an item on the shelf. This image data may be used to generate feature data associated with the user and the item, which may be analyzed by one or more classifiers for identifying an interaction between the user and the item. The systems and techniques may then generate interaction data, which in turn may be analyzed by one or more additional classifiers for identifying an event, such as the user picking a particular item from the shelf within the environment. Event data indicative of the event may then be used to update a virtual cart of the user.

Abstract: A routing system of a call center determines a plurality of advisor clusters to be assigned to each of a plurality of lead records stored in a lead model database. The predictive machine learning model inputs lead model data and advisor model data into a clustering analysis. Various modeling data are extracted from source lead data, sales data, and advisor data, in which the advisor data has been flattened for modeling. The predictive machine learning model applies a combination of a clustering analysis, a cluster model, and an aggregate conversion model to lead model data and user model data. The clustering analysis utilizes unsupervised clustering and supervised clustering, and outputs a plurality of advisor clusters and sales conversion scores. The clustering analysis clusters each of the advisors into one of the plurality of advisor clusters based on degree of similarity of a clustering vector.

Abstract: Examples described herein relate to apparatuses and methods of providing real-time notifications on affordability and advisability of purchasing goods or services using augmented reality. The method includes receiving, from AR device associated with a user, visual data representing a view through a viewing area of the AR device. The visual data comprises geolocation data indicating a geolocation of the AR device. The method includes identifying an image of an object included in the visual data. The method includes determining, based on the visual data, a product identifier associated with the object. The method includes determining an attempt by the user to purchase the object. The method includes generating, in response to determining the attempt, recommendation data based on the product identifier and an account associated with the user. The method includes sending the recommendation data to the AR device to cause the AR device to display the recommendation data to the user.

Abstract: Disclosed are systems, methods, and devices for managing a personal user inventory. In one embodiment, the method comprises retrieving a message associated with a user identifier, the message including a body content portion; identifying a parser associated with the message; parsing the body content portion using the parser to identify an item of merchandise present within the body content portion, wherein the item of merchandise is associated with an item identifier and a set of item details; associating the item of merchandise with the user identifier; and generating a display listing merchandise associated with the user identifier, wherein the listing of merchandise includes the item of merchandise.

Abstract: Systems and method for mapping the location of a product in a store make use of images of products on shelf modules to identify the location of a product. In one implementation, a central computer receives a first image from a camera showing a subset of electronic shelf modules in the store and an indicia displayed thereon. The indicia on a selected one of the subset associated with a particular product or product is subsequently changed. The central computer then receives a second image from the camera showing the changed indicia such that the first and second image can be compared to identify the location of the shelf module and/or product within the store. In another implementation, coordinates of a scanner within one image are utilized to outline borders corresponding to the positioning of products in another image to map the location of a product in a store.

Abstract: A computer-implemented method includes determining a set of target listings, retrieving a seed image associated with the seed listing, the seed listing is categorized within a first item category, and generating a seed item feature vector for the seed image using a convolutional neural network (CNN) trained with images of items. The method also includes identifying a plurality of feature vectors associated with the first item category, comparing the seed item feature vector to the plurality of feature vectors using a k-nearest neighbors (kNN) algorithm, and generating a set of nearest neighbor listings to the seed listing. The method further includes storing the set of nearest neighbor listings as associated with the seed listing, selecting one or more nearest neighbor listings from the set of nearest neighbors, and presenting the one or more nearest neighbor listings as a recommendation to a user of the online e-commerce system.

Abstract: A network node associated with a retail store receives digital images from customers who have initiated a customer transaction at a first location. The digital images are unique and are associated with the transaction. The transaction is then temporarily suspended. To resume the transaction, the customer provides information describing features of the previously provided digital image. The network node uses this information to locate the corresponding digital image, and thus, the corresponding suspended transaction, and to authenticate the customer to resume the transaction. Provided the customer is authenticated, the node resumes the suspended transaction.

Abstract: According to an example, a model is selected from models including an augmented buyer model based on probabilities of conceivable transitions, and each conceivable transition includes a multi-step transition between a first URL and a second URL via at least one intermediate URL of the website. A user is determined to likely be a buyer or a non-buyer based on interaction data and the selected model. The user is presented with an offer that encourages the user to buy from the website upon the determination that the user is a buyer.

Abstract: A system is provided for use in managing waste services performed by a service vehicle. The system may include a sensor configured to capture during completion of a waste service activity an image of waste set out for retrieval by the service vehicle, a portal, and a processor in communication with the sensor and the portal. The processor may be configured to execute instructions stored in memory to receive from a consumer via the portal at least one of a picture and a description of a desired item, to recognize an object in the image captured by the sensor, to make a determination regarding matching of the object with the desired item, and to selectively cause a notification to be displayed on the portal based on the determination.

Abstract: A system for obtaining user parameters of e-commerce users to auto complete checkout forms includes one or more processors configured to monitor user interactions of a user with a merchant website on a user device; determine an intent to purchase one or more items based of the monitoring; determine an unfilled template of a checkout form associated with the merchant website based on previously stored website information, wherein the unfilled template of the checkout form comprises a plurality of checkout form fields; determine one or more user parameters associated with the user device; apply a machine learning algorithm to predict a geolocation of the user device based on the one or more user parameters; and auto fill the at least one of the plurality of checkout form fields in the unfilled template of the checkout form based on the predicted geolocation.

Abstract: Embodiments of the present invention provide a communicable integration of a user network of devices and a vendor system. Embodiments receive, at the vendor system from the user network of devices, a request for provisioning of products by a vendor; determine a provisioning location for provisioning of the products by the vendor; continuously identify a real-time location of the user via the one or more components of the user network of devices; continuously calculate a real-time first limit based on the continuously identified current location of the user and the provisioning location; calculate a total time to provision the products comprising a sum of a product preparation time and the real-time first limit; and optimize delivery of the products based on the total time to provision and the real-time location of the user.

Abstract: Systems and methods to select a product title are described. The system identifies a set of item listings respectively describing items being offered for sale on a network-based marketplace. Each item listing includes a product identifier that matches and is not associated with a product title on the network-based marketplace. Each item listing also includes an item title. The system extracts feature values from the item listings and processes the feature values. The system evaluates the feature values to adopt a product title from an item title included in the set of item titles. The system generates a product user interface including the product title. Finally, the system communicates the product user interface, over a network, for display on a client machine. The product user interface includes the product title.

Abstract: A method, apparatus and computer program product are provided for electronic transactions based on a reply message. In the context of a computer executed method, the method includes receiving a message, from a sender device, including a reply to buy (RTB) identifier associated with a promotion and a RTB validation code. The method also includes authenticating, using a promotion and marketing service host, the RTB validation code, associating the message from the sender with a recipient identifier, and causing the transmission of a purchase order message to the recipient device based on the RTB identifier.

Abstract: A method for providing a recommendation to an individual about an article of footwear includes receiving data about the individual from a sensor module associated with the individual during a first athletic activity engaged in by the individual, determining a first characteristic about the individual's gait based on the data related to the first athletic activity, providing a recommendation about a first article of footwear to the individual based on the first characteristic, receiving data about the individual from the sensor module associated with the individual during a second athletic activity engaged in by the individual, determining a second characteristic about the individual's gait based on the data related to the second athletic activity, comparing the first characteristic with the second characteristic, and providing a recommendation about a second article of footwear to the individual based on the comparison.

Abstract: Provided is a transaction system that supports a transaction between a plurality of consumers and a plurality of suppliers, the transaction system including a server computer that is connected to a network, in which a plurality of consumer-side computers of the transaction and a plurality of supplier-side computers of the transaction are connected to the network, in which the server computer includes a processor that performs processing for interposing in a transaction performed between at least one of the plurality of consumer-side computers and at least one of the plurality of supplier-side computers, and a memory that records consumer-side information regarding the transaction which is output from each of the plurality of consumer-side computers and supplier-side information regarding the transaction which is output from each of the plurality of supplier-side computers.