An advertising method, device and system, and a computer-readable storage medium are provided. The method includes: acquiring user information; sending the user information to a server that stores an advertising requirement, wherein the advertising requirement includes an advertisement content and an advertising condition of the advertisement content; receiving an advertising instruction of the advertisement content from the server, wherein the advertising instruction of the advertisement content is generated by the server when the user information meets the advertising condition of the advertisement content; and playing the advertisement content in response to the advertising instruction.

A system and method for multi-channel dynamic advertisement testing. The system comprises a multi-platform adaptive ad campaign manager, a dynamic advertisement engine, a campaign database, and an omnichannel text-based communicator. The system receives customer interactions with two advertisement test variants, establishes a real-time media stream between a customer device and a second user device, and monitors the media stream to collect data related to effectiveness of the advertisement variants. The system may analyze media stream data together with a plurality of other data types to statistically determine which of the two advertisement variants resulted in better performance based on a variety of advertisement metrics. The system may use the plurality of data and the statistical analysis to suggest an advertisement element to be altered in the next round of advertisement variant testing. This system can combine data collection and analytics for an ad campaign together into one system.

A system and method provides for the use of a proprietary platform to predict impressions and to predict and design ad campaigns. Specifically, a proprietary programmatic advertisement platform correlates television programming asset sources with actual viewing behavior of broadcasts associated with the television programming assets and ad content associated with the ad campaign. The correlation produces a predicted performance value used to generate an ad campaign. For instance, the invention enables television programming asset sources and viewership information providers to communicate with the programmatic advertisement platform in a way that adds value to or otherwise facilitates the valuation of the television programming asset sources in context of the particular ad. Thus, the programmatic advertisement platform delivers improved performance and lower effective cost of television ad campaigns by using automation for simplification and advanced targeting algorithms to reach desired audiences more efficiently.

Computer software architectures are disclosed that use improved machine learning techniques for computer data security, data science, and data privacy protection. Computer operations are improved by more efficiently and effectively processing relevant data, such as web browsing history data. Web browsing data that are representative of web browsing history based on activity associated with a web browser application determined. Using a base model and based on the web browsing data, federated machine learning applied to past web browsing data representative of past web browsing history associated with other web browser applications other than the web browser application can be used to generate an updated targeted model.

A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform: generating linkage scores between nodes at least based on a machine learning model; creating links between the nodes to form connected components based on the linkage scores exceeding a predetermined threshold; generating an actual matching linkage set of the nodes linked in the connected components by using a relaxed blocking criteria; and generating a quality score for the connected components. Other embodiments are disclosed.

Systems and methods of distributing campaign media are disclosed. In some embodiments, a campaign data structure is obtained related to campaign media. Additionally, audience data structures are obtained, wherein each of the audience data structures describes a corresponding audience of a plurality of audiences. Using a computer device, at least one target audience is selected for the campaign media from the plurality of audiences based on the campaign data structure and the audience data structures. Also using the computer device, one or more electronic transmissions of the campaign media are scheduled to at least one user device associated with the at least one target audience based on the campaign data structure and the audience data structures.

A method for interpreting messages, user-defined alert conditions, voice commands and performing an action in response is described. A method for annotating media content is described. A method for presenting additional content associated with media content identified based on a fingerprint is described. A method for identifying that an advertisement portion of media content is being played based on a fingerprint derived from the media content is described. A method of one media device recording particular media content automatically in response to another media device recording the particular media content is described. A method of concurrently playing media content on multiple devices is described. A method of publishing information associated with recording of media content is described. A method of deriving fingerprints by media devices that meet an idleness criteria is described. A method of loading, modifying, and displaying a high definition frame from a frame buffer is described. A method of recording or playing media content identified based on fingerprints is described.

Subject innovations are directed towards a churn model using dynamic state-space modeling to determine churn risks for each active subscriber of a service provider having exhibited a precise sequence of behaviors. The churn model identifies complex behavioral patterns that are consistent with those of subscribers who have churned in a defined past, allowing for a personalized determination of churn risk. The churn model may also use static contextual data to assist in refinement of the churn model through identification of subscriber segments. A churn index is produced that may be used by an automated contextual marketing model to refine decision making for selectively marketing to a subscriber based, in part, on that individual subscriber's churn risk.

A system and method for optimizing at least one of a promotion, a targeting of the promotion, and a campaign associated with the promotion. Acceptances of the promotion are received following each user's selection of the promotion. Information representing users is received from publisher computing devices. Thereafter, respective match keys are generated that are usable to access information representing transaction accounts of each of the users. The match keys are transmitted computing device(s) having access to information representing transaction accounts. Information representing a selected one account is received. For users who redeemed the promotion, the promotion is associated with the selected one transaction account. Thereafter, as a function of the received selection of the transaction account and/or associating the promotion with a selected one transaction account, the at least one processor optimizes the promotion, a targeting of the promotion to other users, and/or a campaign associated with the promotion.

One embodiment provides a method for augmenting missing values in historical or market data for deals. The method comprises receiving information relating to a set of deals. For any service included in one or more deals of the set of deals but not included in one or more other deals of the set of deals, the method further comprises augmenting, for any or all of the one or more other deals that does not include the service, one or more missing values for the service with one or more recommended values based on a recommendation algorithm. The service may be at any service level of a hierarchy of services.