Abstract: Disclosed are methods, systems, and non-transitory computer-readable medium for targeting bid and position for a keyword. For instance, the method may include obtaining information about the keyword, the information about the keyword including observations of value with respect to position for the keyword. The method may further include applying a Gaussian Process Model on the observations to obtain a prediction function and associated uncertainties, the prediction function and the associated uncertainties relating positions to expected values; applying a Thompson sampling reinforcement learning model on the expected values and the positions to obtain a target position; and applying a bid model to the target position to obtain bid information for the keyword. The method may also include transmitting a bid message to a search engine, the bid message including the bid information.

Abstract: Automatic item placement recommendation is described. An item placement configuration system receives an item for which a recommended placement is to be generated and identifies an entity associated with the item. The item placement configuration system then identifies a multi-domain taxonomy that describes relationships between different entities based on items associated with the different entities published among different domains. A representation of the entity associated with the item to be placed is then identified within the multi-domain taxonomy, along with a representation of at least one similar entity. Upon identifying a similar entity, historic item placement metrics for the similar entity are leveraged to generate a placement recommendation for the received item. In some implementations, the placement recommendation is output with a visual indication of a similar entity and associated performance metrics that were considered in generating the recommended placement.

Abstract: One or more embodiments herein can facilitate a process to guide a user at a digital medium. An exemplary system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components can comprise an obtaining component that obtains user behavior data from a digital medium, the user behavior data defining an interaction of the user with the digital medium, a prediction component that, based on the user behavior data, predicts a path of the user within the digital medium, and a classification component that, based on the user behavior data and on the path prediction, classifies a position of the user along a defined path to a conversion objective of the digital medium. The conversion objective can comprise obtaining the user as a customer, achieving a financial transaction, or presentation of a communication.

Abstract: Systems, methods, and computer program products are provided for auctioning advertising inventory for various applications, including for mobile applications. In various embodiments, a request for an advertisement is received at a first server from a client device. The request is sent, from the first server, to two or more remote servers. A bid value and an asset to be presented at the client device is received from each of the two or more remote servers. A highest bid is determined from the received bid values. Whether the asset associated with the highest bid is compliant based on the request is determined. When the asset is determined to be compliant, the asset is sent to the client device.

Abstract: Disclosed are methods, systems, and non-transitory computer-readable medium for targeting bid and position for a keyword. For instance, the method may include obtaining information about the keyword, the information about the keyword including observations of value with respect to position for the keyword. The method may further include applying a Gaussian Process Model on the observations to obtain a prediction function and associated uncertainties, the prediction function and the associated uncertainties relating positions to expected values; applying a Thompson sampling reinforcement learning model on the expected values and the positions to obtain a target position; and applying a bid model to the target position to obtain bid information for the keyword. The method may also include transmitting a bid message to a search engine, the bid message including the bid information.

Abstract: Techniques for a secure and flexible distributed job processing between a transaction network of a service provider and a processing endpoint of an entity are described. In an example, a transaction instrument may be used for a transaction and may be registered with the processing endpoint based on a transaction account. The transaction network may store an ownership object associating a token corresponding to the transaction instrument, a user identifier unique to a user account, and a provider identifier unique to the transaction account. The transaction network may identify a membership status of the user account and may customize the transaction based on this status. The transaction, as customized, may be completed by sending the provider identifier and data about the customization to the processing endpoint.

Abstract: Techniques for providing webpages based on tracking consumer device interactions are discussed herein. Some embodiments may include one or more servers configured to: receive a request for access to a promotion webpage from a consumer device, wherein the request includes a consumer device cookie and the promotion webpage includes an indication of a promotion; in response to receiving the request for access to the promotion webpage, generate the promotion webpage including widgets; generate clickstream data based on tracking widget views of the widgets within the promotion webpage; associate the clickstream data with the consumer device cookie; and generate widget analytic data based on the clickstream data. The widget analytic data may then be used to populate webpages with widgets to optimize various criteria, such as widget views or promotion purchases.

Abstract: A mobile device may include a location determination device, a mobile application, a plurality of wireless communication devices, and a user interface for the mobile application. The mobile device may be coupled, via wireless connections, with a wearable device to capture identification information of the object and a remote portal to determine whether a data warehouse coupled with the portal stores a predetermined type of data associating the identification information and the mobile device. If so, the mobile device may generate an alert on the mobile device and prompt the user to accept an operation related to the object. If the user accepts the operation, the mobile application may monitor the location of the mobile device and initiate the operation based on the location of the mobile device.

Abstract: Classification of the user of an attention application is moved from the cloud, where the classification is performed by advertisers based on trackers that follow a user, to the attention application itself. A user of the attention application controls inputs to the classification model and can exclude sensitive privacy information from inclusion in the classification model. The classification model is applied locally at the attention application to a catalog of advertisements and without revealing to trackers and advertisers whether attention was paid to particular ads. An analytics provider may have increased access to attention applications and can form ad campaigns and provide performance data thereon to advertisers without infringing attention user privacy. The system directs value away from trackers and advertisers and to attention application users and publishers.

Abstract: A method for managing reward value related to a transaction account is described. The method includes receiving a redemption request; generating a reward cost based on at least a conversion rate and a transaction amount; updating a reward value in an account profile to place a hold on an amount of the reward value equivalent to the reward cost; and deducting a deduction amount from the reward value.

Abstract: Advertisement user feedback data may be collected and provided to an advertisement decision engine. Advertisements may be presented to users via various electronic media such as digital television, Internet, software, etc., and advertisement feedback user interfaces may be provided to users in connection with such advertisements. An advertisement feedback user interface may be provided via the same electronic medium and device as the corresponding advertisements, or via a different electronic medium and/or device. User feedback data regarding electronic advertisements, as well as additional related data, may be received and provided to one or more advertisement decision engines. An advertisement decision engine may use the advertisement user feedback data to determine a future advertisement to be presented to one or more users at an advertisement insertion opportunity identified in one or more various electronic media.

Abstract: A method is disclosed. The method includes receiving an authorization request message for a transaction from an access device. The authorization request message includes a value and an account identifier. The user device is used by a user to conduct a transaction with the resource provider. The method also includes determining an activity metric associated with the user of the user device, determining a value alteration based at least in part on the activity metric, and applying the value alteration to the value for the transaction.

Abstract: For providing a targeted advertisement to a user, a referral server sends, to a financial platform server, a request for fetching the financial information of the user. The referral server receives, from the financial platform server, a reply containing the financial information of the user. The referral server analyses the financial information of the user to determine one or more behavioural attributes of the user. The referral server uses the one or more behavioural attributes of the user to define a behavioural profile of the user. The referral server may send to a device of the user a code sequence related to a marketing campaign selected according to the behavioural profile of the user. The marketing campaign may be selected by calculating a conversion rate for each of a plurality of marketing campaigns.

Abstract: Techniques for a secure and flexible distributed job processing between a transaction network of a service provider and a processing endpoint of an entity are described. In an example, a transaction instrument may be used for a transaction and may be registered with the processing endpoint based on a transaction account. The transaction network may store an ownership object associating a token corresponding to the transaction instrument, a user identifier unique to a user account, and a provider identifier unique to the transaction account. The transaction network may identify a membership status of the user account and may customize the transaction based on this status. The transaction, as customized, may be completed by sending the provider identifier and data about the customization to the processing endpoint.

Abstract: Disclosed are methods, systems, and non-transitory computer-readable medium for targeting bid and position for a keyword. For instance, the method may include obtaining information about the keyword, the information about the keyword including observations of value with respect to position for the keyword. The method may further include applying a Gaussian Process Model on the observations to obtain a prediction function and associated uncertainties, the prediction function and the associated uncertainties relating positions to expected values; applying a Thompson sampling reinforcement learning model on the expected values and the positions to obtain a target position; and applying a bid model to the target position to obtain bid information for the keyword. The method may also include transmitting a bid message to a search engine, the bid message including the bid information.

Abstract: A method includes determining that a token associated with a customer is present in a store; and sending, to a mobile device associated with the customer, a signal to prepare the mobile device to be able to receive a marketing offer.

Abstract: A mobile device may include a location determination device, a mobile application, a plurality of wireless communication devices, and a user interface for the mobile application. The mobile device may be coupled, via wireless connections, with a wearable device to capture identification information of the object and a remote portal to determine whether a data warehouse coupled with the portal stores a predetermined type of data associating the identification information and the mobile device. If so, the mobile device may generate an alert on the mobile device and prompt the user to accept an operation related to the object. If the user accepts the operation, the mobile application may monitor the location of the mobile device and initiate the operation based on the location of the mobile device.

Abstract: A computer implemented device is described that is adapted for improving memory efficiency for conducting machine learning on multi-dimensional vectors stored as specially configured data structures. The device includes network interfaces adapted for receiving data sets and communicating with data harvesting applications, as well as data storage and memory for storing the configured data structures. The multi-dimensional vectors and the system provide a data architecture that processes disparate data sets to programmatically extract features transformed from raw information, the extracted features stored in the form of data values suitable for conducting data approximations and neural network processing.

Abstract: Techniques for providing webpages based on tracking consumer device interactions are discussed herein. Some embodiments may include one or more servers configured to: receive a request for access to a promotion webpage from a consumer device, wherein the request includes a consumer device cookie and the promotion webpage includes an indication of a promotion; in response to receiving the request for access to the promotion webpage, generate the promotion webpage including widgets; generate clickstream data based on tracking widget views of the widgets within the promotion webpage; associate the clickstream data with the consumer device cookie; and generate widget analytic data based on the clickstream data. The widget analytic data may then be used to populate webpages with widgets to optimize various criteria, such as widget views or promotion purchases.

Abstract: A method is disclosed. The method includes receiving an authorization request message for a transaction from an access device. The authorization request message includes a value and an account identifier. The user device is used by a user to conduct a transaction with the resource provider. The method also includes determining an activity metric associated with the user of the user device, determining a value alteration based at least in part on the activity metric, and applying the value alteration to the value for the transaction.