Abstract: A system for processing images captured in a retail store and automatically identifying products displayed on shelving units, includes at least one processor configured to: receive a first image depicting a shelving unit with a plurality of products of differing product types displayed thereon and a first plurality of labels coupled to the shelving unit; receive a set of second images depicting a second plurality of labels; correlate a first label depiction of a specific label included in the first image to a second label depiction of the same specific label included in a second image; use information derived from the second label depiction to determine a type of products displayed in the first image in proximity to the specific label; and initiate an action based on the determined type of products displayed in proximity to the specific label.

Abstract: A method for generating a related product interface portion in an electronic user interface based on user-generated text includes identifying, for each product of a plurality of products, one or more respective characteristics from end user-generated text associated with the product, whereby a plurality of characteristics are identified for the plurality of products. The method further includes determining a plurality of characteristic groups, each group comprising two or more of the plurality of characteristics, wherein the characteristics within a group are similar to each other; receiving, from a user through the electronic user interface, an input related to a product category; and in response to receiving the user input, generating and presenting the related product interface portion that includes a respective product from each of the two or more of the characteristic groups related to the category.

Abstract: Methods, systems, and computer program products for facilitating user selection using trend-based joint embeddings are provided herein. A method includes obtaining a selection of an item in an online catalog; determining a compatible item of the plurality of items at least in part by providing the selected at least one item and at least one previously selected item corresponding to the user to a trend-based machine learning model, wherein the trend-based machine learning model is trained on historical data associated with the item in the online catalog and fine-tuned based on current trend data from multiple data sources; receiving feedback in response to outputting the at least one compatible item; identifying one or more attributes related to the at least one compatible item based on the feedback; and using the trend-based machine learning model to determine at least one additional compatible item based on the one or more attributes.

Abstract: A processor device has a CPU cooperating with an input device and an output device, under control of stored instructions, and is arranged to receive service requests at the input device, assign service requests received in successive time periods to respective batches of requests; access stored service provider data to identify available service providers from among a pool of service providers; after completing the assignment of service requests to a batch, perform a matching process to endeavour to match each service request of the batch of requests to a service provider; and for each service provider to whom a match is made, output a notification of the respective potential match from the output device.

Abstract: Item vectors representing transaction contexts for items are mapped to multidimensional space. A request is received for an alternative to a given item from a resource. The multidimensional space is evaluated to identify closest candidate items to the given item based on the corresponding item vectors. An optimal candidate item is selected from the candidate items based on the request. The association between the given item and the optimal candidate item is injected within a process workflow associated with the resource.

Abstract: Computer-implemented methods, computer systems, and computer readable media for determining, sorting, or determining and sorting a set of items. The method includes receiving, via a user device, parameter values from a user and receiving parameter weights. The method further includes determining a sort score for each vehicle of a set of vehicles based on the received parameter values and parameter weights, and sorting the set of vehicles based on the sort score of each vehicle of the set of vehicles.

Abstract: A computer-implemented method may include receiving a customer submission for a vehicle from a customer device, the customer submission including a plurality of customer criteria; receiving a request from the customer device to provide the customer submission to a merchant device; and receiving a reply from the merchant device, the reply including a plurality of merchant criteria. The computer-implemented method also may include determining a variance between the customer criteria and the merchant criteria, and transmitting, to the merchant device, at least one of the variance or the customer criteria.

Abstract: A method and apparatus for a commerce platform providing proof of application ownership of a network distributable application are described. The method may include receiving a request to approve an application developed by a merchant system, wherein the application includes an application programming interface (API) component, a software development kit (SDK) component, or a combination thereof provided by the commerce platform to the merchant system. The method may also include generating a unique identifier (ID) for the application to be included as metadata within the application. Furthermore, the method may include obtaining, from an application information system, data describing the application, and extracting an ID from metadata in the data obtained by the application information system.

Abstract: A centralized accounting system for invoice generation is described as a web-based portal accessible by parties of a supply chain finance relationship via one or more computer networks. The centralized system provides a computer-based, network accessible platform in which a customer and a vendor may negotiate and agree upon terms of a purchase order for products. The centralized system then approves the purchase order based on vendor and customer profile information, and sends a notification of the approved purchase order to a bank. The centralized system automatically generates a vendor invoice for the approved purchase order and submit the vendor invoice to the bank for payment according the terms of the supply chain finance relationship. The centralized system ensures that the vendor invoice is accurate for the approved purchase order. The centralized system may also automatically generate and submit a bank invoice to the customer for the approved purchase order.

Abstract: A system and method for dynamically displaying a digital representation of one or more recommended print products on a user interface of a computing device is provided. The method comprises providing a digital representation of each of a plurality of print products stored in a computer memory, wherein the plurality of print products are categorized into at least one of a plurality of print product groups that include a first print product group; identifying a geographic location or a time of year; selecting the first print product group using the processor of the computing device, wherein the first print product group is selected based on the identified geographic location or time of year; and displaying the digital representations corresponding to at least one of the plurality of print products included within the first print product group on the user interface. Other aspects are also disclosed.

Abstract: A method of allowing a user to scan products and obtain product recommendations based on the user's personal biological/genetic data, using a cartridge to perform a test on the data in conjunction with a test control system into which the cartridge is plugged. A user account is created and is associated with a cartridge ID that is read from the cartridge by the tablet and is also read using the wearable user device and passed via the test control system to a server when the wearable user device is coupled to the test control system. The test control system communicates test results to the server which analyses the test results to generate analysis results. The analysis results are then downloaded to the wearable user device via the test control system or some other channel. Product codes are also downloaded and stored to the wearable user device.

Abstract: This disclosure describes systems, methods, and devices related to predictive modeling for evaluating vehicles. A device may receive a customer identifier (e.g., a user identification number, a social security number, driver license number, etc.). The device may retrieve credit data associated with the user identifier and vehicle data associated with a vehicle. The device may determine a first weight for the credit data and a second weight for the vehicle data. The device may determine, based on the first weight and the second weight, a value. The device may determine whether or not the value exceeds a profitability threshold. The device may determine a loan information associated with the customer identifier. The device may send a first indication of the product or service to a user device for presentation. The device may send a second indication of the loan information to the second device for presentation.

Abstract: This application relates to apparatus and methods for automatically determining and providing digital recommendations including discounted items with associated savings. In some examples, a computing device obtains savings data including savings items. In response to obtaining the savings data, the computing device obtains a plurality of clusters. Each cluster of the plurality of clusters includes a set of product types. The computing device obtains user data associated with a user, and based on the savings data and the plurality of clusters, determines a set of initial items for recommendation. The set of initial items includes a subset of the savings items. The computing device also determines final recommendation items for the user based on the set of initial items and the user data.

Abstract: According to certain aspects of the disclosure, a computer-implemented method may be used for providing vehicle recommendations based on traffic camera data. The method may include acquiring traffic data from a plurality of traffic cameras and determining vehicle information based on the traffic data. Additionally, calculating average idling time of vehicles based on the traffic data from the plurality of traffic cameras. Additionally, determining accident information based on the traffic data from the plurality of traffic cameras and selecting at least one available vehicle for purchase, wherein the at least one available vehicle matches one or more predetermined requirements based on the determined vehicle information, average idling time, and the determined accident information. Additionally, transmitting a recommendation based on the selected at least one available vehicle for purchase.

Abstract: A cross-entity and cross-retailer platform is provided that captures transaction data, indexes, and stores the data in a cloud-accessible data store. A service is provided that custom processes retailer and entity-defined workflows based on purchase transactions using the data store. The service also generates and maintains correlations between items, the transactions, geographical locations, retailers, and stores of the retailers. The correlations are provided as timely retail recommendations to the retailers and entities for suggested changes that are likely to optimize purchase transactions. The entities may comprise manufacturers of an item, a supplier of the item, a distributor of the item, and a Consumer Packaging Goods (CPG) company of the item.

Abstract: A system for viewing shopping information on a social networking platform is disclosed. At the social networking platform, the system receives a request from a user device corresponding to a first user of the social networking platform to view a list of a second user of the social networking platform. The list may include items offered for transaction on a network-based commerce server. In response to receiving the request from the user device, the system forwards the request to the network-based commerce server, and then receives updated information for at least one item on the list from the network-based corner server. Then, the system communicates the updated information received from the network-based commerce server to the user device.

Abstract: An online concierge system uses a machine learning click through rate model to select promoted items based on user embeddings, item embeddings, and search query embeddings. Embeddings obtained by an embedding model may be used as inputs to the click through rate model. The embedding model may be trained using different actions to score the strength of a customer interaction with an item. For example, a customer purchasing an item may be a stronger signal than a customer placing an item in a shopping cart, which in turn may be a stronger signal than a customer clicking on an item. The online concierge system generates a ranking of candidate promoted items based on the search query and using the click through rate model. Based on the ranking, the online concierge system displays promoted items along with the organic search results to the customer.

Abstract: Product recommendations are selected according to a model. Product recommendations may be annotated with rules of the model used to select the products. A user may modify the model and be provided with a URL and a cookie associated with the modified model. Subsequent requests or the URL and presenting the cookie are processed using the modified model. A context may be associated with the cookie and modified by the user to observe performance of the model for the context. An interface may permit a user to specify rules for the model or otherwise model its behavior. User interactions with a website result in recommendations according to the model. A journey is recorded that records content, recommendations, and parameters of the model corresponding to the recommendations. The journeys of users may be filtered and visually presented to a user.

Abstract: A data processing system generates recommendations for on-line shopping by scoring recommendations matching the customer's cart contents using by assessing and ranking each candidate recommendation by the expected incremental margin associated with the recommendation being issued (as compared to the expected margin associated with the recommendation not being issued) by taking into consideration historical associations, knowledge of the layout of the site, the complexity of the product being sold, the user's session behavior, the quality of the selling point messages, product life cycle, substitutability, demographics and/or other considerations relating to the customer purchase environment.

Abstract: A computer implemented method for controlling operational states of a hardware matching processor includes monitoring, by a circuit breaker, incoming electronic data transaction request messages to the hardware matching processor; dynamically defining a range of values as a function of values included with electronic data transaction request messages received during a rolling lookback window; detecting that an incoming electronic data transaction request message contains a value outside the range of values; transitioning the electronic data transaction processing system into a pre-open state for a predetermined period, thereby preventing the hardware matching processor from matching incoming electronic data transaction request messages; calculating a pre-open value at an end of the pre-open state; and re-opening the electronic data transaction processing system at the calculated pre-open value, thereby allowing the hardware matching processor to match incoming electronic data transaction request messages.