Aspects of the subject disclosure may include, for example, providing to a user device a video content item including at least one scene which includes a plurality of advertisement placement opportunities and determining a preference profile for an individual associated with the user device. Aspects further include selecting a group of matching advertisements having advertisement profiles that match the preference profile for the individual and determining a relative prominence score for each advertisement placement opportunity. Aspects further include ordering the matching advertisements according to prominence information specified for each matching advertisement, wherein the prominence information corresponds to a relative desired prominence specified by an advertiser associated with the matching advertisement. Aspects further include providing the ordered matching advertisements to the user device according to the respective prominence information so that a matching advertisement having a greatest desired prominence is displayed in the video content item at an advertisement placement opportunity having a highest relative prominence score. Other embodiments are disclosed.

An approach is provided for determining the context-aware similarity between applications. A similarity platform processes one or more context logs associated with one or more devices to determine one or more context intents. The similarity platform further determines one or more distributions of one or more applications executed at the one or more devices with respect to the one or more context intents. The similarity platform also determines a context-aware similarity between two or more applications based, at least in part, on the one or more application distributions.

Aspects of the subject disclosure may include, for example, a method, operating at a processing system including a processor, can include receiving a reply message from a communication device responsive to a query signal and including audio information collected at a presentation area, determining consumer presence information at the presentation area according to the audio information collected at the presentation area, determining a probability of a consumer advertising experience according to the consumer presence information, selecting first advertising media from a set of advertising media according to the probability of consumer advertising engagement, and presenting the first advertising media to the presentation area via the presentation system. Other embodiments are disclosed.

Systems and methods for redeeming a reward held by an individual are described. A method for redeeming a reward includes determining threshold criteria for provision of a targeted reward redemption offer, identifying at least one individual based upon the threshold criteria, determining the targeted reward redemption offer, and providing the targeted reward redemption offer to the identified individual. A response to the provided targeted reward redemption offer may be received, and an account of the identified individual may be adjusted in accordance with the targeted reward redemption offer and the received response.

Aspects of the subject disclosure may include, for example, a method in which a processing system obtains physical and social environmental data for a communication device user, and provides content for presentation at the device. First reaction data, obtained via sensors associated with the user, indicate the user's reaction to presentation of the content; the data is analyzed to determine user affinity for the content in a context of the physical and social environments. The content is modified during the presentation; second reaction data is obtained and analyzed to determine a second user affinity for the modified content. If the affinity is enhanced, the modified content is sent to other users' equipment via a social network. Affinity responses regarding the modified content are analyzed, and a set of users is identified as an affinity group; additional content is transmitted to equipment of the affinity group. Other embodiments are disclosed.

In a system for dynamically selecting messages for display on a mobile device, the message to be displayed is selected based on a change in one or more parameters associated with the user of the device. The parameters include a set of promotions previously transmitted to the user device or a purchasing pattern of one or more other users to whom a particular promotion was sent previously.

A method and system for managing digital media campaigns accesses a set of programming data that contains various attributes of media assets that a media service provider will present to users. A media advertising campaign manager receives various criteria for the inclusion of advertisements in a particular entity's advertising campaign. The system uses the attributes in the data set to develop an advertising campaign that satisfies the entity's criteria. In various embodiments, the method system may consider the entity's preferences, seller criteria, and campaign requests for other entities.

Systems and methods for controlling ad delivery to mobile clients while maintaining user privacy are herein provided. One exemplary method involves a location broker service. The method includes receiving, at an ad delivery service, a location use token from a mobile client, which may be a single use token. The method includes sending, from the ad delivery service, the location use token to the location broker service for verification at the location broker service. The method includes receiving, at the ad delivery service, the mobile client location from the location broker service based on the verification. The method includes delivering, from the ad delivery service, a location-targeted ad to the mobile client at the mobile client location, where the delivering is further based on a geographic density of a plurality of mobile clients. An advertiser using the ad delivery service may be billed based on location use token history.

Methods, systems, and computer programs are presented for the determination of optimal communication scheduling. One method includes an operation for training a machine-learning program to generate a frequency model that determines a frequency for sending communications to users. The training utilizes training data defined by features related to user information and responses of users to previous communications to the users. The method further includes determining, by the frequency model and based on information about a first user, a first frequency for the first user. The first frequency identifies the number of communications to transmit to the first user per period of time. Further, the method includes operations for receiving a communication request to send one or more communications to the first user and determining send times for the one or more communications to the first user based on the first frequency. The communications are sent at the determined send times.

Disclosed here is a system that can obtain attributes of an advertisement, where an attribute has a continuous value, and a range of acceptable values is uncertain. The system can create a file including contents that when provided to a predetermined function produce a value of the attribute. Based on the file, the system can generate values corresponding to the attributes. Based on the generated values, the system can create the advertisement. The system can obtain a response data to the created advertisement and can fit a multidimensional function to the attributes and the user response data. Based on the multidimensional function, the system can determine next values and next ranges, where the next values and the next ranges indicate an improvement in the response data.