Abstract: Systems and methods for predictive gift subscriptions are provided. A gift subscription service may store a gift subscription and a profile associated with a gift recipient. The gift subscription service may then identify a time to send a gift to the gift recipient and associate a computational model with the gift recipient and the profile. When the gift subscription service determines a change in the profile, the gift subscription service may then update the computational model associated with the gift recipient in real-time by applying a machine learning algorithm to the change in the profile and use the updated computation model to formulate a prediction for the gift recipient that may then be used to identify a set of gifts to present to the gift recipient. The gift subscription service may then present the set of gifts to the gift recipient.

Abstract: A system may include a platform for an application to support processing flows for a service provider, such as ordering, sales, support, service delivery, and related process flows. The system may provide a limited set of application programming interfaces (APIs) that map to an application's user-experience page flows. The APIs may always appear to the application that the interaction process completed successfully—even if human intervention is required—to allow the application to complete the transaction. The system may have the ability to recognize the same user, and leverage that user's behavior across interactions with multiple sales channels. The system may thus provide, in one aspect, an enhanced user experience for ordering and maintaining complex service and equipment offerings.

Abstract: Global shoppers may access numerous predetermined online shopping websites. Users can shop normally and can generate a third-party cart. Foreign shipping addresses and foreign payment types may be accepted.

Abstract: In various exemplary embodiments, a system and an associated method to retrieve information related to marketplace items within an electronic environment are disclosed. A network architecture comprises a listing module to store the information related to the marketplace items. The related information includes one or more user-created items such as an image of a model with one or more tagged items worn by the model. Each of the one or more tagged items has associated descriptive metadata. A communications module is arranged to receive a query including search terms related to social fashion items from an end-user. A query engine is coupled to the communications module to match the search terms contained within the query to the associated descriptive metadata of the tagged items in the listing module. A processing module then displays to the end-user the model and the one or more tagged items.

Abstract: In some cases, a delivery service system may include a handheld electronic device for use with a delivery service (e.g., a grocery delivery service). When operating in a voice input mode, the handheld electronic device may record and store audio data in memory. The stored audio data may be communicated from the handheld electronic device (e.g., via a Wi-Fi connection) to the delivery service for speech processing. When operating in a scanner input mode, the handheld electronic device may record and store item identifier information (e.g., barcode data) in memory. The stored data may be communicated to the delivery service for item identification processing. In some cases, a user interface associated with the delivery service may allow the user to review and confirm an order prior to submission of the order for delivery.

Abstract: Systems and methods for automated product recommendation are disclosed herein. This can include generating an entry, the entry corresponding to an item selected for purchase, in a mirror-cart linked with a user account and identifying a recipe associated with the selected item. This can include comparing items identified in the recipe to items contained in the mirror-cart to identify a missing item that is not in the mirror-cart, and then prompting the user to purchase the missing item. Automated product recommendation can include generating an entry in the mirror-cart linked to the missing item when the user selects the missing item for purchase, updating an invoice with price information for the selected missing item, and transferring the invoice to a point of sale terminal at the retail location.

Abstract: Methods and apparatus are disclosed regarding an e-commerce system having social networking aspects. The e-commerce system leverages such social networking aspects to help promote the sale of products.

Abstract: Disclosed are methods, systems, and non-transitory computer-readable medium for automatic product comparison using price comparison with reward redemption options indicating relative price reduction.

Abstract: An intelligent store system and an intelligent store method are provided. The method includes: sensing, by a proximity sensor, whether there is a first customer approaching the proximity sensor; sensing, by an image sensor, a movement trajectory of the first customer; and determining whether the first customer is entering or leaving a store in response to the first customer approaching the proximity sensor sensed by the proximity sensor. If the first customer is entering the store, a first virtual identity and a first virtual shopping cart corresponding to the first virtual identity are generated for the first customer, and a first product list of the first virtual shopping cart is updated according to the movement trajectory. If the first customer is leaving the store, a first operation of the first customer is received by a human machine interface, and the first product list according to the first operation is updated.

Abstract: Methods and systems are disclosed for providing a vehicle suggestion to a user based on image analysis. The method may include: receiving one or more vehicle images via website data associated with the user; identifying one or more first-level traits from the one or more vehicle images; obtaining one or more vehicle identifications from the one or more vehicle images based on the one or more first-level traits; determining a value of each of the one or more first-level traits and/or the one or more vehicle identifications via one or more algorithms; determining the vehicle suggestion based on the value of each of the one or more first-level traits and/or the one or more vehicle identifications; and transmitting, to a device associated with the user, a notification indicating the vehicle suggestion.

Abstract: Systems and methods for machine-based matching of lodging inventory from a plurality of disparate reservation provider systems address the difficulties inherent in comparing prices to obtain a lowest possible price, which difficulties are inherent in the distribution of inventory to multiple third-party reservation providers who are generally permitted to utilize their own naming conventions when describing lodging inventory and who are also free to at least some extent to set prices for the various lodging inventory within their control. The systems and methods match room types using information obtained from the multiple third-party reservation providers, whereby direct comparisons can be made between prices for the same room types even when the reservation providers do not utilize identical descriptions or naming conventions for the respective room inventories.

Abstract: A method includes receiving a training metric, the training metric indicating a parameter to be optimized by content recommendations. A machine learning algorithm maybe used to determine a plurality of different combinations of the recommendation algorithms in the experiment, and each of one or more of the plurality of combinations may be used to generate a content recommendation for one or more visitors. The statistical performance of each of the one or more combinations in optimizing the parameter (based on the content recommendations generated by those combinations) may be monitored and a higher percentage of visitors may be allocated to a combination that generates content recommendations that are the most effective at optimizing the parameter.

Abstract: System and method to streamline the checkout process of e-commerce websites is disclosed. The processing subsystem includes a web crawler to browse the e-commerce websites, a website analysis module to analyze checkout data entry forms and web UI of the corresponding e-commerce websites browsed by the web crawler. The processing subsystem includes a classification module to classify the checkout data entry forms into fields based on a form data model. The classification module maps user information with classified fields using a natural language mapping technique to obtain a mapped model. The processing subsystem includes a fingerprinting module to fingerprint configurations and checkout pages of the corresponding e-commerce websites to obtain fingerprinting data. The processing subsystem includes a checkout processing module to generate a one-click checkout flow for an e-commerce website selected from the e-commerce websites.

Abstract: Systems and methods for remote interactive inspection services may comprise receiving a communication associated with a property from a mobile device. In response to the communication, an audio-visual remote presence connection may be established with the mobile device. Video of a portion of the property may be portrayed via the audio-visual remote presence connection. Authentication data may be transmitted. The authentication data may be configured to enable access to a lockbox located at the property.

Abstract: Systems and methods relating to recommending vehicles similar to a first vehicle based on telematic data and vehicle manufacturing data and using machine learning techniques, and systems and methods for ranking recommended vehicles according to evaluation criteria are disclosed.

Abstract: Methods, systems, and computer-readable media for catalog item selection based on visual similarity are disclosed. A similarity detection system selects candidate items for an unavailable item in a catalog. The candidate items are selected from one or more item categories in which the unavailable item is classified. The system determines respective similarity scores for at least some of the candidate items with respect to the unavailable item. For a particular candidate item, the similarity score is determined based at least in part on a visual similarity between an image of the unavailable item and an image of the particular candidate item. The system selects, from the candidate items, a set of visually similar items to the unavailable item based at least in part on the similarity scores. The visually similar items are available to the user.

Abstract: Systems and methods relating to recommending vehicles similar to a first vehicle based on telematic data and vehicle manufacturing data and using machine learning techniques, and systems and methods for ranking recommended vehicles according to evaluation criteria are disclosed.

Abstract: Systems and methods relating to recommending vehicles similar to a first vehicle based on telematic data and vehicle manufacturing data and using machine learning techniques, and systems and methods for ranking recommended vehicles according to evaluation criteria are disclosed.

Abstract: A system receives item data corresponding to an item list from a user. The item list may include one or more items. The system communicates the item list to a community group associated with the user and the system then receives member data from one or more members of the community group, wherein the member data is associated with the one or more items on the item list.

Abstract: A method of segmenting a plurality of users in a first region based on predicted activity external to the first region. A system and computer program product are also provided.