A user identifies products offered by the user to an online system. The online system identifies a product offered by the user in an image by applying a identification model to the image. If the online system identifies a product in the image with at least a maximum confidence value, the online system automatically tags the post with metadata about the product or suggests a tag to the user. If an object in the image could be one of multiple products, the online system identifies the multiple products to the user, which may be ordered based on confidences of matching the object, allowing the user to select which product is in the image. If the unlisted identifies a product in the image with less than a minimum confidence value, the online system identifies the user's offered products and suggests that the user select a product.

A method and system for conducting an online payment transaction through a point of sale device. The method includes receiving input from a user selecting an item for purchase through the point of sale device; calculating a total purchase amount for the item in response to a request from the user to purchase the item; and sending payment authorization for the total purchase amount from the point of sale device to a payment entity, in which the payment authorization is sent to the payment entity via a mobile communication device of the user. The method further includes receiving a result of the payment authorization from the payment entity through the mobile communication device; and completing the payment transaction based on the result of the payment authorization.

A system for advertisement space recommendation and a checkout process is provided. The system includes an advertisement space recommendation module determines an expected network traffic for each product. The advertisement space recommendation module determines expected profits corresponding to merchants based on expected network traffic and generates a recommendation corresponding to a set of advertisement space to the merchants for selling the products. The system includes an auction module enables the merchants to bid for the set of advertisement space to exhibit the corresponding products. The system includes a checkout URL generator module creates a distinctive URL for the set of advertisement space and enables one-click checkout process for the products displayed on the set of advertisement space on an advertisement platform based on URL for each product across merchants.

A food product recommendation system may include a camera configured to obtain an image of a food product area having available food products and a remote device associated with a given user. The system may also include a recommendation server configured to cooperate with the remote device to obtain a desired food product characteristic from the given user and determine recommended food products from the available food products based upon the desired food product characteristic. The recommendation server may also be configured to associate a corresponding food product identifier to each recommended food product and communicate the recommended food products to the remote device. The remote device may display the image of the food product area with the recommended food products augmented with the corresponding food product identifiers and obtain user selection for purchase of at least one of the recommended food products based upon the corresponding food product identifier.

Automatically communicating information related to a user computing device from a central computing system to a transaction computing system prior to initiation of a transaction between the user computing device and the transaction computing system comprises a digital wallet application and a central computing system. A digital wallet application receives a beacon signal from a transaction computing system indicating the specific identification of the terminal with which the user intends to conduct a transaction. The user computing device communicates the terminal identification to the central computing system. The central computing system communicates customer data, such as loyalty information and offers, to the transaction computing system associated with the terminal. The transaction computing system communicates the customer data to the terminal. When the user taps the user computing device to initiate the transaction, the terminal provides any benefits associated with the customer data.

Systems and methods are described herein for analyzing messages and other information provided in relation to a web communication, a mobile application communication session, a phone communication, or another type of communication. For example, a system and method are provided for initiating a text message communication session between an agent and a user. A two-way communication session may be facilitated between the user and the agent. A mobile telephone number disclosed by the user during the two-way communication session may be detected, and a text message communication session between the user and the agent may be initiated if a mobile telephone number was detected. Availability status associated with a provider of items or services may also be analyzed to determine an agent for communicating with the user.

Computer-implemented methods of providing personalized recommendations to a user of items available in an online system, and related systems. First-level features including context features are computed based upon context data. A first-level machine learning model is then evaluated using the first-level features to generate predictions of user behavior in relation to a plurality of individual items available via the online system. A list of proposed item recommendations is constructed based upon the predictions. Second-level features are computed based upon the context data and list features based upon the list of proposed item recommendations and the corresponding predictions generated by the first-level machine learning model. A second-level machine learning model is evaluated using the second-level features to generate a prediction of user behavior in relation to the list of proposed item recommendations. A personalized list of item recommendations is provided based upon the prediction generated by the second-level machine learning model.

Examples described herein relate to a system consistent with the disclosure. For instance, the system may comprise a data lake including information relating to an in-store activity of a customer and an online activity of the customer, a processing resource, and a non-transitory machine-readable medium storing instructions executable by the processing resource to identify the in-store activity and the online activity of the customer, aggregate and store the in-store activity and the online activity of the customer in the data lake, reduce an amount of products in a product portfolio, compare purchases including in-store purchases and online purchases, and recommend a product of the plurality of products based on the comparison.

Concepts and technologies are disclosed herein for providing augmented reality shopping displays. A processor can execute a shopping service. The processor can receive a request for display data. The processor can analyze shopping data to identify data sources, the shopping data can include user data associated with the requestor, and the data sources can include an offer source. The processor can obtain collected data from the data sources identified, the collected data including an offer. The processor can generate display data based upon the collected data and the shopping data, and provide the display data to a user device. The display data can identify the offer.

The present invention provides a processing system (10) including an acquisition unit (11) that acquires, from each of a plurality of terminal apparatuses, first identification information for identifying the terminal apparatus or a facility where the terminal apparatus is placed, and biological information of a customer input to the terminal apparatus, an authentication unit (12) that performs customer authentication, based on the biological information of the customer, a history registration unit (13) that, when customer authentication is successful, registers, in visit history information of the customer, a facility determined by the first identification information, and a provided information generation unit (14) that generates, based on the visit history information and attribute information of the facility, provided information to be provided to the customer.