A method, apparatus, and computer program, each configured for determining a travel propensity, the travel propensity being a distance a customer is willing to travel to redeem a renderable data object, are provided An exemplary method comprises classifying each of a plurality of geographic regions as one geographic region type of a plurality of geographic region types, mapping each of a plurality of redemption locations to a geographic region type, calculating, for a first geographic region type, a first distance that accounts for a predefined number of redemptions, determining a number of merchants having redemption locations within the first distance, calculating a second distance, from a center of a geographic region of the second geographic region type, necessary to include the number of merchants having redemption locations within the first distance, and assigning the second distance as the second geographic region type travel propensity.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for using machine learning models to expand user groups while preserving user privacy and data security are described. In one aspect, a method includes receiving, for a web-based resource, a set of user group identifiers for a set of user interest groups that each include, as members, one or more users that requested content from the web-based resource over a given time period. A seed user list that includes user identifiers for at least a portion of the users in the set of user interest groups is created. A similar audience machine learning model is generated based on a set of one or more feature values corresponding to one or more features of the users corresponding to the user identifiers in the seed user list. A set of similar users is identified using the model.

A method of generating a visualization of location-dependent values is provided where a plurality of bids and a plurality of supply locations are received from at least one datastore. Each of the plurality of bids has an associated location. A first geographic location is selected from the plurality of supply locations. A ball tree is generated, the ball tree comprising a plurality of nodes, each node of the ball tree comprising a pivot geographic location and a radius, each node corresponding to at least one local value having a location within the radius of the pivot. The ball tree is traversed to generate sorted collection of location dependent values. Each of the location dependent values is determined from one of the plurality of bids. A map of the collection of location dependent values is output.

A method comprises receiving as input one or more spatial temporal factors associated with one or more products where the one or more spatial temporal factors affect a demand for one or more product attributes of the one or more products at one or more locations at a select period of time and dynamically modifying a first option plan based on the received input of the one or more spatial temporal factors to generate a second option plan for a given location of the one or more locations at the select period of time. The steps are performed by at least one processor device coupled to a memory.

An approach is provided that receives multimedia content and extracts a set of metadata from the content. The extraction of metadata includes performing image analysis on the multimedia content. The approach then analyzes the set of metadata with the analysis resulting in a set of regulations that apply to the multimedia content. The approach compares the set of metadata to the set of regulations and allows publication of the multimedia content when the comparison reveals that the multimedia content is in compliance with the set of regulations, and inhibits publication of the multimedia content when the multimedia content fails to comply with the set of regulations.

A method, computer system, and computer program product for providing spatial weather map data to the visually impaired are provided. The embodiments may include receiving a weather map image that contains weather information and a subject of interest, wherein the subject of interest comprises a user current location, a business location, or an asset location. The embodiments may also include receiving a request from a user for current time, historical or forecast data depicted in the weather map and a request for a geo-location of the subject of interest. The embodiments may further include generating sounds corresponding with the requested weather map data, wherein the generated sounds appear to the user to originate in a particular direction and at a particular distance from the subject of interest, wherein the apparent location of the sounds correspond with a weather map feature including the location of approaching or surrounding weather.

A method for retargeting in a system including a plurality of vehicles having exteriors configured to convey messaging to occupants of other vehicles. Communication signals including information relating to time-stamped locations of the vehicles are received. Time-stamped location data including a first plurality of the time-stamped locations is provided to a mobile location data aggregator. A first set of anonymized identifiers associated with mobile device users known to be within exposure zones associated with the time-stamped locations is received from the mobile data aggregator. The first set of anonymized identifiers is provided to an audience data service provider, which returns other anonymized identifiers associated with the first set of anonymized identifiers. An augmented exposed audience is formed by adding the other anonymized identifiers to the first set of anonymized identifiers. Advertisements are caused to be provided to devices corresponding to at least a subset of the augmented exposed audience.

The disclosed subject matter relates to a system and method for personalizing customer experience at a retailer’s physical location in order to increase sales and customer satisfaction. The personalization is based upon classification of customer’s online interaction with the retailer. Upon detecting the customer’s presence at the retailer’s physical location, data of the customer’s online interactions is retrieved and classified based on the type of online interactions and temporal characteristics. Push content is transmitted to the customer, the push content being based upon at least the classification and data associated with retailer’s physical location.

Systems and methods include determination of a plurality of call map clusters, each call map cluster associated with a respective type of external call, two or more of a plurality of services, and a service call model modelling, for each of the two or more of the plurality of services, the issuance of outgoing service calls in response to received service calls. A bot is deployed proximate to each of the plurality of services, and each deployed bot is associated with a respective configuration to issue outgoing service calls in response to received service calls as modelled by the service call models for each of one or more services proximate to the deployed bot.

An all-encompassing system for planning and optimizing scheduled delivery appointments (or attended deliveries) through the utilization of a software tool having two major constituents: an asynchronously operating background advanced, genetic route optimization algorithm and an algorithm-informed communication user interface (whether through digital, or even analog, pathways, such as, without limitation, SMS, email, IM, and the like, oral communications, or any other possible means of communication). Such a system employs the optimization algorithm to determine efficient routes for delivery services in response to selections from contacted customers via the communication user interface. In this manner, the system allows for an initial base route generation from a set population of responding customers and negotiation through the communication user interface for a delivery time in relation to such a route. Subsequent responses are introduced in relation to the route in efficient manner by the algorithm as well.