Abstract: Systems, methods, devices, and computer readable storage media described herein provide techniques for generating recommendations utilizing a heterogeneous distance function. In an aspect, a measure of relevancy between a first data item and a second data item is received. A setting of an adjustable parameter of a parameterized heterogeneous distance function is determined based on the measure of relevancy. The parameterized heterogeneous distance function comprises first and second sub-functions. The first sub-function calculates a distance between data items based on features of a first data type and the second sub-function calculates a distance between data items based on features of a second, different, data type. A recommendation system is caused to utilize the parameterized heterogeneous distance function to generate a recommendation based on received input. In a further aspect, the measure of relevancy is determined as a function of a measure of interactions and a measure of impressions.

Abstract: A golf system includes one or more processing circuits including one or more memory devices coupled to one or more processors. The one or more memory devices are configured to store instructions thereon that, when executed by the one or more processors, cause the one or more processors to associate an identifier of a respective player assigned to a golf cart with the golf cart, monitor at least one of locations of the golf cart about a golf course or purchases made on the golf course associated with the identifier, and update a player profile for the respective player based on the identifier and the at least one of the locations of the golf cart or the purchases.

Abstract: Embodiments of the present disclosure provide an information processing method and apparatus, and a device, the method includes: sending an information request to a platform side at a preset time interval if it is determined that a merchant platform application has been logged in; receiving a system message sent by the platform side in response to the information request in real time, where the system message is sent by a service side to the platform side in real time; and displaying the system message and/or prompt information of the system message on the merchant platform application. This embodiment does not require the merchant to obtain a new system message by refreshing a page, avoiding a repeated refresh operation by the merchant and avoiding the merchant missing an important notification due to not being able to obtain the system message in time.

Abstract: A method for transferring ownership of an asset via an online raffle includes receiving asset information including a minimum selling price (in raffle tokens) and a maximum listing duration for a raffle of the asset. The method further includes providing a representation of the asset via a user interface based on the asset information. The method further includes issuing raffle tokens. The method further includes receiving an asset selection including a pledged amount of raffle tokens. In response to a value of aggregate pledged raffle tokens satisfying the minimum selling price during the listing duration, the method includes: probabilistically selecting a raffle token; determining a consumer associated with the selected raffle token; and providing a notification to the consumer, including an offer to transfer ownership of the asset. In response to acceptance of the offer, the method includes transferring ownership of the asset to the consumer.

Abstract: A computer-implemented method for obtaining one or more recommendation candidates for items of content available via a content distribution system, the method comprising: obtaining user data for a selected user, wherein the user data comprise or represent user activity and/or content metadata associated with user activity; generating or otherwise obtaining relationship information for at least some content metadata associated with the available content; generating further user data from the user data using the relationship information so that the further user data comprises or represents alternative content metadata that are distinct or at most overlap with the content metadata associated with the user activity; performing a content recommendation process using at least the further user data and content information for the available content to generate one or more content recommendation candidates for the user.

Abstract: Various methods and systems are provided to capture a unique product code, such as QR code, on a mobile device, process the information contained in the code, provide the user with options of making a purchase, including purchasing a plurality of selected products from different captured codes, and processing the payment via the user's mobile device.

Abstract: Methods, systems, and computer-readable media are provided for providing information on electronic visual displays in retail stores. In one implementation, a door for a retail storage container may include one or more electronic visual displays. In one implementation, the electronic visual display may be connected to a shelf in the retail store. In one implementation, an image of products in a retail store captured using at least one image sensor may be obtained, and the image may be analyzed to determine a condition of products of a particular product type. Further, based on the determined condition of the products of the particular product type, at least one display parameter may be selected for a particular item, and the selected at least one display parameter may be used to display the particular item on an electronic visual display in the retail store.

Abstract: The present disclosure relates to a service providing apparatus and method for cross-recommendation between product sales sites based on online, a service providing system for the apparatus and method, and a non-transitory computer readable medium having a computer program recorded thereon for calculating and matching similarity between product categories of different product sales sites on the basis of an analysis result according to behavior history analysis of a customer for a plurality of different product sales sites based on online and the apparatus and method recommending a product on the basis of the category of a specific product sales site with high similarity to a recommendation category of another product sales site when the customer visits the specific product sales site on the basis of the matching result.

Abstract: According to the embodiments of the present disclosure, a method, an apparatus, a device, a storage medium and a program product for object determination are provided. The method includes: recalling, from a set of objects, a plurality of candidate objects for a target promoter, the promoter being capable of publishing a guidance content for guiding a user to acquire a corresponding object; determining, based on a first feature of the target promoter and second features of the plurality of candidate objects, priority levels of the plurality of candidate objects; and determining, based on the priority levels, a target object for the target promoter from the plurality of candidate objects.

Abstract: A language model is utilized to generate a recommendation for a user of an online system to update a current order. The user is grouped into a cluster of users based on how likely is that the user will not use a credit before expiration. A prompt for input into the language model includes information about the cluster, content of a cart, and information about the credit. Based on the prompt, the language model generates a risk score for the user representing a likelihood of the user not using the credit. The online system identifies, based on the risk score and the content of cart, a quantity of an item for recommendation to the user. A user client device displays a user interface with a suggestion for the user to include the quantity of the item in the cart and use the credit for purchasing the suggested quantity of item.

Abstract: According to a present invention embodiment, a system for processing an order in a computerized environment identifies an item selected by a user in the computerized environment. The system determines that a provider of the item is unable to provide the item to a delivery location based on one or more conditions. A bidding session is conducted for a plurality of service providers to select one or more service providers with services enabling the item to be provided to the delivery location. A transaction for the item is performed to deliver the item to the delivery location via the provider of the item and the one or more service providers. Embodiments of the present invention further include a method and computer program product for processing an order in a computerized environment in substantially the same manner described above.

Abstract: Embodiments of a supply chain management system (SCMS) are disclosed that enable the generation of synthetic supply chain activity data for developing machine learning models, such as models for predicting vendor lead times (VLTs) of purchase orders fulfilled by a supply chain network. In embodiments, the generation process is performed over successive time periods to simulate dynamically changing variables of the supply chain network, including inventory levels, product demand, and stock manager decisions. The generation process may also be used to generate synthetic data to simulate elements within the supply chain network, such as simulated warehouses, vendors, or products. The disclosed SCMS is able to generate highly realistic training data that simulates the operations within the supply chain network, which can be used to improve the performance of machine learning models.

Abstract: An electronic device is provided. The electronic device includes a communication circuit for communicating with a server, a display, at least one processor connected, and a memory, wherein the memory stores instructions causing, when executed, the at least one processor to collect an intermediate operation value corresponding to an item to which a user responds among first items introduced to the user through the display, store the collected intermediate operation value, receive item information about second items and intermediate operation values, input, as an input value, the intermediate operation values received from the server, input first user information indicating a profile of the user and the user response item vector, obtain scores assigned to each of the second items from a result value output from the recommendation model, and provide the item information to the user through the display on the basis of the scores.

Abstract: A power trading system includes: a matching-related data acquiring unit that acquires demand bid information and supply bid information, the demand bid information and the supply bid information each being given a priority level; an appearance rate prediction unit that obtains a predicted appearance rate of the demand bid information and that of the supply bid information; an agreement rate prediction unit that obtains a predicted agreement rate of the demand bid information and that of the supply bid information; and a matching unit that matches the demand bid information to the supply bid information while switching a priority level, based on the predicted appearance rate and the predicted agreement rate.

Abstract: An embodiment uses a computer-implemented approach to identify and automate workstreams from common actions in online applications. A browser extension collects and processes user event metadata, which is used to train machine learning models for workflow automation. The extension reads relevant fields from web services and delivers prompts with high-level actions (HLAs) based on user or organizational details. These HLAs are appended to prompts and sent to a large language model (LLM) via an API call. The LLM responds with a solution and a sequence of actions, which the browser extension executes automatically. Users retain control to pause, accelerate, or modify these actions. This method ensures secure, end-to-end workflow automation across various computing devices, enabling efficient and autonomous resolution of tasks while maintaining user oversight. The browser extension processes metadata, not enterprise data, ensuring security and privacy.

Abstract: Dynamic recommendations based on customer profiles is described. A computing system may receive, in association with a visit of a customer to a merchant location of a merchant, an identifier (ID) of the customer. The computing system may access, based at least in part on the ID, a customer profile of the customer. The computing system may access item availability data indicating whether items are in stock at the merchant location. The computing system may generate, based at least in part on the customer profile and the item availability data, a recommendation(s) associated with an item(s) that is in stock at the merchant location. The computing system may receive an indication that the customer is at the merchant location, and in response to the receiving of the indication, the computing system may determine a server, and cause an electronic device of the server to output the recommendation(s).

Abstract: It is determined that a device associated with a subscriber is accessing an online system of a service provider. Data usage information associated with the subscriber as accessed. Based on the data usage information, an offering from a plurality of offerings is selected, the offering including a service offering or a product offering. Information that identifies the offering is caused to be sent to the device for display.

Abstract: The present invention provides a system for determining a commodity or service suitable for a user. The system is configured to perform: acquisition of data and/or information regarding the user (step S701); calculation of a score that multi-dimensionally represents a feature of the user on the basis of the acquired data and/or information regarding the user (step S702); and determination of a commodity or service suitable for the user, by using the score (step S703).

Abstract: Various embodiments are directed to apparatuses, methods, computer-readable media, computer program products, and systems related to detecting a process trigger that identifies a target entity; identifying, entity data associated with the target entity; generating, using a machine learning based prediction model, a predictive asset output based at least in part on the entity data, wherein the predictive asset output comprises at least one predicted asset; generating, using a dynamic contextualization model, a multifactor contextualized asset representation for the at least one predicted asset based at least in part on the at least one predicted asset and the entity data; and transmitting the multifactor contextualized asset representation to one or more computing devices via one or more communication channels.

Abstract: An online system automatically generates a personalized collection of items around a theme. The online system generates a prompt for input into a language model, the prompt including information about a plurality of items and a text describing the theme around which the collection of items will be built. The online system requests the language model to generate, based on the prompt, a list of products eligible for building the collection of items. The online system accesses a computer model trained to identify a set of items personalized for a user of the online system. The computer model identifies, based on the list of eligible products and information about the user, the set of items for populating the collection of items. The online system causes a device of the user to display a user interface with the collection of items for inclusion into a cart of the user.