Abstract: A method for generating a unique and personalised MMS message having a redeemable component enables the instant delivery and receipt of individual and personalised, trackable, rich media messages direct to any mobile user.

Abstract: A control apparatus is configured to control advertisement data presented to an occupant of a movable object having an automated driving function, and includes a travel road specification unit for specifying a road scheduled to be travelled by the movable object corresponding to the destination, a setting unit for setting, according to the road scheduled to be travelled, a switching recommendation point for switching a driving mode of the movable object from automated drive to driver-led manual drive, a notification plan generation unit for setting a degree of importance of the advertisement data to be presented according to the driving mode for the road scheduled to be travelled, and generating a notification plan for presenting the advertisement data to the occupant according to the set degree of importance, and a notification control unit for presenting notification data including the advertisement data to the occupant according to the notification plan.

Abstract: A method, apparatus, and system are directed towards providing advertisement insertions at a point of consumption into digital content, such as broadcast television content. A content provider may initially mark the content for advertisement insertion, and create a metadata file indicating constraints, targets, expirations, or the like. A downstream user employs a plug-in component and provides an initial user profile, in part, to access the content with advertisements. As the content is played, and an advertising marker is encountered, fast forwarding or other skipping features are disabled, and an advertisement stream is spliced into the content stream. The advertisement stream is determined based on the user profile and/or other metadata. Moreover, the advertisement stream may be obtained over a network such that advertisements may be refreshed even years after the content has been acquired by the user. In one embodiment, the advertisement consumption may be tracked and reported.

Abstract: Herein disclosed are systems and methods for distributing fractional equity rewards to users of a loyalty platform based on tracked user loyalty purchases. The disclosed systems and methods may reduce time between a user loyalty purchase and distribution of a fractional equity reward determined based on the user loyalty purchase. In one example, by maintaining a pre-purchased supply of shares within an inventory account of the loyalty platform, and by distributing fractional equity rewards to user accounts on the loyalty platform from the pre-purchased supply, a reduction in reward distribution time may be enabled. Further, by maintaining the pre-purchased supply of shares of stock within the inventory based on a running average rate of fractional equity reward distribution, and predicted events, the amount of stock in the inventory may be intelligently controlled to reduce excess inventory, while reducing a probability of reward distribution delay.

Abstract: Methods and apparatus to generate consumer data are disclosed. An example method of selecting a sample of transaction data corresponding to a membership program includes defining a first type of member of the membership program; defining a second type of member of the membership program; calculating, via a processor, a target for the sample; selecting, via the processor, a first portion of the transaction data for the first type of member in accordance with the target; generating, via the processor, an updated target by recalculating the target with the first portion of the transaction data removed from consideration; and selecting, via the processor, a second portion of the transaction data for the second type of member in accordance with the updated target.

Abstract: Identifying a change of an indicator value for a system of interdependent entities includes determining the indicator value, logging input data for the system of interdependent entities, logging scoring payload data and related results of a machine-learning model used as part of the system of interdependent entities, wherein the scoring payload data are derived from the input data, clustering the input data into a number of clusters resulting in defined clusters, determining metric values of the machine-learning model by mapping each of the defined clusters onto the scoring payload data resulting in a vector of metric values, re-determining the indicator value for each defined cluster, resulting in a vector of re-calculated indicator values, and determining correlation matrix values for a matrix between the vector of re-determined indicator values and the vector of the metric values for each of the defined clusters.

Abstract: A content influencer scoring system may include influencer computers each associated with a respective content influencer having influencer historical performance data and legacy influencer content associated therewith. A remote server may obtain advertisement campaign data associated with an advertisement campaign and parse the advertisement campaign data for advertisement keywords. The remote server may match content influencers to the advertisement campaign data based on the advertisement keywords and, for each content influencer, generate an advertisement campaign score.

Abstract: Offers are distributed by providing a plurality of offers to a first user and directing the first user to distribute the offers to selected additional users. The plurality of offers may be customized by the system based on the first user's previous interactions with the system, and may be further customized by the first user before sending the offers to the selected additional users. The additional users may include any user including known and/or unknown users and/or contact in the first's user networks including business and/or social networks. The system may also track and store information relating to the distribution, access, and redemption of the offer by the first user and the selected additional users and provide additional incentives based upon the access and redemption, and based upon interactions between the first user and the selected additional users.

Abstract: Aspects of the invention perform an operation comprising receiving a plurality of rules associated with a first seat in a mass-transit vehicle, determining a plurality of physical attributes for a first passenger, of a plurality of passengers, based on data describing the first passenger received from a plurality of data sources, determining a plurality of non-physical attributes for the first passenger based on the received data describing the first passenger, determining that at least one of the plurality of physical attributes and the plurality of non-physical attributes of the first passenger satisfy each rule in the set of rules associated with the first seat, computing, based on a machine learning (ML) model a score for the first passenger, determining that the score exceeds a threshold score associated with the first seat, and allocating the first passenger to the first seat in the mass-transit vehicle.

Abstract: A visual discovery tool for automotive manufacturing with network encryption, data conditioning, and prediction can include an extraction device configured to receive data records from application-specific file source databases. The tool can further include a vehicle alert database that receives the vehicle records from the plurality of extraction databases. The visual discovery tool can include at least one hardware processor in communication with the extraction device and the vehicle alert database. The tool can be configured to selectively restrict access to an interactive display based on whether a client device receives authorization credentials.

Abstract: The present disclosure relates to a system, method, and computer program for automatic coupon code fill in a mobile application. The system identifies a checkout page in a WebView of a mobile application and extracts field data from the checkout page. The system identifies a coupon code field and a cart total field from the field data. The system obtains one or more coupon code(s) and tests the one or more coupon code(s) in the checkout page. The one or more coupon code(s) are tested in the identified coupon code field to determine whether any of the coupon code(s) cause the value associated with the cart total field to decrease. In response to one or more coupon code(s) providing a reward on the checkout page, the system identifies a best coupon code, which it inserts in the identified coupon code field in the checkout page in the mobile application.

Abstract: A process for controlling device use, the process comprising: receiving, from a first user having a token credit amount, a request to use a play app having a required token amount; determining a play response based on the token credit amount, wherein the determination corresponds to the following: if the token credit amount is greater than the required token amount, then the request is granted; and if the token credit amount is less than the required token amount, then the request is denied.

Abstract: In certain aspects, the disclosed implementations include methods and systems for dynamically generating and determining transaction affinity relationship information associated with a set of merchants involved in a set of transactions. In certain implementations, the transaction affinity relationship information may reflect affinity relationships between merchant chains in a merchant affinity network. The disclosed implementations may receive an adjustment to an affinity relationship associated with a merchant chain, and based on the adjustment, predicts one or more changes to affinity relationships associated with other merchant chains in the merchant affinity network.

Abstract: Embodiments of the present disclosure relate to data correlation of data pertaining to content distributed through distinct content delivery networks including offline networks and data related to user interaction with an online presence on the distributed computer network and uses for such correlated data, including to measure and quantify latent effects of the content distributed through a distinct content delivery network, such as an offline network, on user's interactions with the online presence on the distributed computer network.

Abstract: Systems and methods relating to machine learning. An edge device runs a new data point on a first neural network and determines activations on the layers within that neural network. The first neural network is a fully trained network based on a second neural network on a server. The activation data for the various layers in the first neural network are, starting with the output layer, sequentially transmitted to the server. The server continuously receives this activation data and continuously compares it with previously encountered activation data for the second neural network. If the received activation data is within an expected range, then the edge device is instructed to stop sending activation data. Otherwise, the server continues to receive the activation data for the other layers until the new data point is received by the server or the activation data is within the expected range of previously encountered activation data.

Abstract: A method and a device for multi-class classification of an application relative to a classification of a transport mode by machine learning, including: (a) sensors configured to measure at successive instants physical quantities specific to said application, and (b) a microprocessor configured to: (b1) acquire said successive measurements from the sensors to calculate predictors from physical quantities of said measurements, (b2) construct continuous series (aj) of samples, each sample being a vector formed of a predetermined number of predictors, (b3) break down each series (aj) of samples into a set of sequences (Sk) each corresponding to a specific class among a set of predetermined classes, (b4) under-sample the sequences associated with the classes among said set of predetermined classes while conserving for each selected sequence a predetermined fraction of samples of said sequence, thereby forming classes associated with balanced samples, and (b5) construct a classifier (F) from said balanced samples b

Abstract: A system for locating an object in a volume of space can include a first electrical device disposed in the volume of space and having a first antenna and a first controller, where the first controller reduces a first default range of the first antenna to a first effective range. The system can also include an object disposed within the first effective range, where the first controller recognizes a first signal, using the first antenna, that identifies the object in the first effective range.

Abstract: A device solves for eigenvalues of a matrix system. The device performs a domain decomposition of a matrix system into non-overlapping subdomains and a reordering of matrices of the matrix system. An interface variable projection subspace associated with interface variables of an adjacency graph of the matrix system is created. The interface variables are related to nodes of the adjacency graph which are connected with nodes located in neighboring partitions. An internal variable projection subspace is created that is associated with internal variables of the adjacency graph of the matrix system, wherein the internal variables are related to nodes of the adjacency graph which are connected only to nodes located in the same partition. A projection matrix is built based on the interface variable projection subspace and the internal variable projection subspace. The device determines eigenvalues that solve a Raleigh-Ritz eigenvalue problem utilizing the projection matrix.

Abstract: In an approach for precipitation detection, a processor trains a first machine learning model for detecting precipitation in a region using a first training set of data including a plurality of historical data from a plurality of mobile devices collected in the region and a plurality of quantitative precipitation estimation data. A processor trains a second machine learning model for detecting a location of a mobile device in the region using a second training set of data including both historical indoor and outdoor data from the plurality of mobile devices collected. A processor receives a current data from the mobile device. A processor determines whether the mobile device is located indoor or outdoor based on the current data. A processor compares the current data against a threshold set in the first machine learning model to indicate precipitation. A processor determines whether the current data exceeds the threshold.

Abstract: A server and a method for generating a user-advertisement (user-ad) matching list for online advertisement is provided. The method includes obtaining profile information and advertisement exposure history information of users exposed to a plurality of advertisements through an ad impression server, obtaining advertisement information of an advertisement to be delivered by an advertiser, identifying candidate users for the advertisement of the advertiser among the users, based on the profile information of the users, predicting an access time when the candidate users will access the ad impression server, selecting target users to be provided with the advertisement of the advertiser among the candidate users, based on the predicted access time, obtaining a preference of each target user for an advertisement product of the advertiser, and generating the user-ad matching list by matching the advertisement of the advertiser with the target users, based on the preference.