Abstract: Techniques are generally described that relate to a method and system for selecting an advertisement for a subscriber of a multi-platform service operating over a transmission medium. An advertisement computer presents advertisements to the subscriber over a platform included in the multiplatform service. Each of the advertisements is associated with a geographic location. The advertisement computer may receive positive responses to the presentment of the plurality of advertisements and define a target geographic area. A plurality of local advertisement responses from the positive responses are selected by the advertisement computer. Each local advertisement response is associated with a location inside the defined target geographic area. The advertisement computer defines a positive response area based on the plurality of local advertisement responses and selects a first new advertisement.

Abstract: A system for providing context sensitive display overlays to a mobile device via a network comprising an overlay datastore, a processor, coupled to the datastore and programmed to receive a request from a mobile device via the network for a list of overlays, determine user context information, search the datastore for overlays matching the user context and provide the list of overlays to the mobile device via the network.

Abstract: A data processing device system may be configured by a program at least to determine particular content associated with a first indication of observable presentation of the visual indicator received from a first device system; store in response to determining that the particular content is associated with the received first indication, a recorded-presentation indication indicating that the particular content or information associated therewith has been device-presented; determine that the particular content is associated with a second indication of a user interaction with the visual indicator received from a second device system; and store in response to determining that the particular content is associated with the received second indication, an indication that the particular content has been interacted with by a user.

Abstract: The Multidimensional Machine Learning Data and User Interface Segment Tagging Engine Apparatuses, Methods and Systems (“MLUI”) transforms ambient condition data, sales data, user interface selections, cognitive intelligence question input inputs via MLUI components into project projections, campaigns, user interface visualizations, cognitive intelligence question output outputs. An update to a survey data file is detected. The updated survey data is stored in a SQL database configured to utilize a composite index of the updated survey data that optimizes database query time. A set of affected entity segment identifiers is determined. A set of affected category identifiers is determined. A set of affected cognitive intelligence (CI) datapoint identifiers is determined as CI datapoint identifiers associated with each combination of an affected entity segment identifier and an affected category identifier.

Abstract: A hybrid, optimized exchange is provided, the hybrid, optimized exchange operably connected to a demand-side platform (DSP), the hybrid, optimized exchange further operably connected to a supply-side platform (SSP), the hybrid, optimized exchange configured to receive an advertising request, the hybrid, optimized exchange further configured to conduct, using a bid floor, a hybrid, optimized DSP auction of the advertising request among a plurality of DSPs, thereby generating a winning DSP that makes a winning DSP bid in an automated advertising auction system after the SSP initiates an SSP auction of the advertising request, the hybrid, optimized exchange optimizing the bid floor provided to the plurality of DSPs in the hybrid, optimized DSP auction and simultaneously optimizing a shading factor used by the hybrid, optimized exchange to place a hybrid, optimized bid on behalf of the winning DSP in the SSP auction.

Abstract: This document describes the collection, generation, distribution, and management of online web content. The devices, systems, and methods described herein can be used to collect and generate online web content and communications. Specifically, the disclosed devices and systems may be employed to produce one or more marketing and/or advertising campaigns, as well as for monitoring, managing, defining the efficiency, effectiveness, and workability of the campaign with respect to generating user engagement, thereby accurately determining the cost benefits of the campaign. The analytic results provided may then be used to guide the generation of original web content, such as for the purposes of enhancing customer or follower experience, driving business, and for driving advertising campaigns. Alternatively, web content that is in the public domain, and determined to perform well, can be reproduced, referenced, or otherwise referred to, in the context of promoting or presenting the user's web content.

Abstract: In some examples, a server may determine that a case, created to address an issue of a computing device, is closed and perform an analysis of steps in a process used to close the case. The analysis may determine a length of time of each step and determine that a time to close the case or complete a particular step was at least a predetermined amount faster than average. The server may use machine learning to create a survey question to determine a technique used to close the case or complete the particular step faster than average and to determine one or more incentives to provide a technician that closed the case. An answer from the technician to the survey question may include the technique used to close the case or complete the particular step faster than average. The technique may be shared with other technicians.

Abstract: Systems and methods for the selection of the promotions are provided. A set of possible offers are initially received, each including a set of variables, with each variable having a set of possible values. These form a combination of variable values for each offer. A heuristic is applied to all possible offers to reduce the number of offers being considered. The combination of variable values for these reduced number offers is converted into a vector value, which is then scored, ranked and the top ranked offers are selected for inclusion in a promotional campaign. The remaining offers are then analyzed to select additional offers to include into the promotional campaign which maximizing a determinant for the selected offers using their vectors. All selected offers are administer in a promotional test campaign across many consumer segments. Feedback from the campaign may be collected to generate a “general” offer.

Abstract: The Multidimensional Machine Learning Data and User Interface Segment Tagging Engine Apparatuses, Methods and Systems (“MLUI”) transforms ambient condition data, sales data, user interface selections, cognitive intelligence question input inputs via MLUI components into project projections, campaigns, user interface visualizations, cognitive intelligence question output outputs. A category identifier selection is obtained via a category selection interaction interface mechanism. Entity segment identifier selections are obtained via entity segment selection interaction interface mechanisms. A set of visualization cognitive intelligence (CI) datapoint identifiers is determined as CI datapoint identifiers associated with each combination of a selected entity segment identifier and the selected category identifier.

Abstract: A method for predicting user purchase by a user of a first site includes: selecting a distribution representing a probability distribution (PD) of inter-purchase-times (IPTs) across the first site and a second other site for each user, assigning each purchase of each user to one of the first site and the second site according to a Stochastic model, combining the selected PD with the Stochastic model to generate a PD of IPTs for only the first online site, estimating parameters of the probability distribution of IPTs for the first site by applying a Statistical modeling approach to features of each user, applying a sequence of observed IPTs of a given user for the first site and the parameters of the given user to the selected distribution to generate a probability, and determining whether the next purchase occurs on the second site based on the probability.

Abstract: The Multidimensional Machine Learning Data and User Interface Segment Tagging Engine Apparatuses, Methods and Systems (“MLUI”) transforms ambient condition data, sales data, user interface selections, cognitive intelligence question input inputs via MLUI components into project projections, campaigns, user interface visualizations, cognitive intelligence question output outputs. A cognitive intelligence (CI) datapoint identifier cache datastructure is generated, the CI datapoint identifier cache datastructure configured to comprise a category identifier and an entity segment identifier. A CI datapoint value cache datastructure is generated, the CI datapoint value cache datastructure configured to comprise a set of module datastructures, each module datastructure corresponding to a module identifier associated with the category identifier, each module datastructure comprising a set of metric datastructures, each metric datastructure corresponding to a set of calculated metrics.

Abstract: A computer-implemented method for determining auction prices of vehicles may include obtaining wholesale auction price data indicative of wholesale auction prices and vehicle attribute values of a plurality of vehicles; grouping the plurality of vehicles into a plurality of vehicle groups respectively associated with a plurality of characteristics; determining a plurality of regression models respectively based on the plurality of vehicle groups; obtaining information describing a target vehicle; based on the target-vehicle values and values for the one or more economic indicators, determining an estimated wholesale auction price of the target vehicle using an identified regression model of the plurality of regression models; determining a discount factor representing an expected discount of a post-repossession auction price of the target vehicle from the estimated wholesale auction price; and determining an estimated post-repossession auction price of the target vehicle based on the estimated wholesale aucti

Abstract: A method, apparatus, and computer program product are disclosed for improved machine learning using a statistical model. In the context of an apparatus, some example embodiments include a processor configured to cause retrieval of information regarding a plurality of consumers, and modeling circuitry configured to train a statistical model of the plurality of consumers based on the retrieved information, and predict, using the statistical model, an incremental booking value associated with the promotion for each consumer of the plurality of consumers. The processor is further configured to select a subset of the plurality of consumers for receiving impressions of the promotion. Some example embodiments may further include communications circuitry configured to transmit an impression of the promotion to each consumer in the subset of the plurality of consumers.

Abstract: In one embodiment, a system, is provided to take not just a person's time and location into consideration, but also has knowledge of and takes into account their availability, their preferences, their schedule, their purpose for being at their current location, and/or their next goal or stop. One embodiment is able to take into account a real-time view of supplier inventory and deduce and make available much better-adapted offerings and support for that person's travels and endeavors. In one embodiment, having an understanding of a rate of conversion and its relation to traffic and weather patterns allows service providers to make more accurate predictions about various items, including but not limited to, conversion rates, offer types, offer upgrades, traffic etc. In yet another aspect of the invention, the information collected from many travelers, and also information collected from airlines and weather observers, etc.

Abstract: Embodiments provide a computer-executed method, a computer system and computer program product for initiating a command. The method includes causing a consumer input definition interface to be displayed on a visual display of a computing device associated with a consumer, wherein the consumer input definition interface includes an indication of a command. The method also includes, while the consumer input definition interface is displayed, receiving input definition data defining a consumer interaction by the consumer. The method also includes generating a compound consumer input based on the input definition data, and associating the compound consumer input with the command and the consumer. The method further includes storing the association between the compound consumer input and the command on a non-transitory storage device so that receipt of the compound consumer input from the consumer automatically initiates the command.

Abstract: A system predicts a value estimate for a user who provides a service that involves moving among geographical regions (e.g., a transportation service). The system determines the value estimate by identifying a sequence of time periods, each time period having an associated set of geographical regions. Possible transitions between geographical regions in different time periods are analyzed, for example, using statistical or machine-learned models, to determine likelihoods that the user will move between the geographical regions from one time period to another, and to determine expected values for a transition. Such models may be trained or developed using historical service data and user profile data stored by the system. Transitions are analyzed over a sequence of time periods to determine accumulated values associated with estimated overall values for each geographical region. The system predicts an overall value estimate for the user based on the accumulated values.

Abstract: Described is a system for learning and predicting key phrases. The system learns based on a dataset of historical forecasting questions, their associated time-series data for a quantity of interest, and associated keyword sets. The system learns the optimal policy of actions to take given the associated keyword sets and the optimal set of keywords which are predictive of the quantity of interest. Given a new forecasting question, the system extracts an initial keyword set from a new forecasting question, which are perturbed to generate an optimal predictive key-phrase set. Key-phrase time-series data are extracted for the optimal predictive key-phrase set, which are used to generate a forecast of future values for a value of interest. The forecast can be used for a variety of purposes, such as advertising online.

Abstract: Systems, computer-implemented methods, apparatus, and/or computer program products that facilitate implementation of child tokens for improved transaction data storage and/or implementation of reduced transaction information payloads for quicker computerized payment processing are provided. In various embodiments, a system can comprise a scanner component that can scan a financial instrument during a current transaction, thereby extracting financial instrument data associated with the current transaction. In various instances, the system can further comprise a logging component, that can identify in an electronic transaction log a first data entry that corresponds to a previous transaction. In various cases, the first data entry can list previous financial instrument data associated with the previous transaction, and the previous financial instrument data can match the current financial instrument data.

Abstract: Embodiments provide a computer-executed method, a computer system and computer program product for initiating a command. The method includes causing a consumer input definition interface to be displayed on a visual display of a computing device associated with a consumer, wherein the consumer input definition interface includes an indication of a command. The method also includes, while the consumer input definition interface is displayed, receiving input definition data defining a consumer interaction by the consumer. The method also includes generating a compound consumer input based on the input definition data, and associating the compound consumer input with the command and the consumer. The method further includes storing the association between the compound consumer input and the command on a non-transitory storage device so that receipt of the compound consumer input from the consumer automatically initiates the command.

Abstract: A control section of a server apparatus as an information processing apparatus in the disclosure executes: inquiring of a terminal of a user who desires to board a self-driving vehicle operating for pickup-delivery of an item, whether or not the user is able to handle work of pickup-delivery of the item at a pickup-delivery location between the self-driving vehicle and a pickup-delivery service user; and when a response indicating that the user is able to handle the work of pickup-delivery when the user is on board the self-driving vehicle is received from the terminal, transmitting to the self-driving vehicle an instruction to allow the user who desires to board and is able to handle the work of pickup-delivery to board the self-driving vehicle.