Provided are systems, methods, and computer-readable medium for operating a content delivery system. In various examples, the content delivery system can transmit a series of queries to a computing device for display in an application executing on the computing device. The content delivery service can receive a first set of responses, and determine from these response an additional series of queries. The additional series of queries can also be transmitted to the computing device. The content delivery service can receive a second set of responses for the additional series of queries. The content delivery service can further use the responses to determine a presentation for a program of content, the presentation including graphics, text, and audio. The content delivery service can transmit the present and the program of content to the computing device, where the computing device can render the presentation to modify an appearance of the program of content.

Aspects of the subject disclosure may include, for example, obtaining first data associated with a first presentation of a first portion of a first video, obtaining second data, wherein the second data is obtained: from a creator of the first video, by performing an analysis on the first portion of the first video, or a combination thereof, identifying an emotional trajectory of a first user during the first presentation in accordance with the first data and the second data, selecting a first creative in accordance with the emotional trajectory, and transmitting the first creative to a first communication device. Other embodiments are disclosed.

Disclosed is a computer implemented method of bidding for advertisement opportunities based on user behavior data. The computer implemented method may include receiving a primary bid value associated with an audience list including a plurality of users. Further, each user of the plurality of users may be associated with user behavior data corresponding to a primary filtering criteria. Further, the computer implemented method may include receiving a secondary bid value associated with a sub-audience list including one or more users. Further, the one or more users may be associated with user behavior data corresponding to a secondary filtering criteria. Additionally, the computer implemented method may include transmitting a bid for an advertisement opportunity based on each of the primary bid value and the secondary bid value. The advertisement may be presentable to the one or more users.

A social network server computer forms a social network including a primary member linked to a plurality of secondary members, each of whom provides a member profile. A network profile is generated based on an analysis of the member profiles. A social network server computer then determines a relative value of the social network with respect to a merchant by analyzing the associated network profile, and offers a merchant incentive to the primary member of the network as a function of the determined relative value. In a second embodiment, a merchant computer associated with a merchant determines a relative value of the social network with respect to a merchant by analyzing the network profile, and offers a merchant incentive to the primary member of the network as a function of the determined relative value. The merchant incentives may be also offered to the secondary members of the associated social network.

An online system may identify content with which a user has an interest. For example, the online system may determine that a user has an interest in the content based on interaction information indicating that the user interacted with the content. In a particular example, the online system may identify image concepts included in the content based on computer vision techniques that recognize the image concepts. The online system may model probabilities that image concepts will appeal to users. Based on the modeled probabilities, the online system may automatically recommend image concepts for inclusion in candidate images, automatically generate candidate images, or assess candidate images to determine a probability of user interaction with the assessed candidate images.

A plurality of anonymized publisher-user identifiers are received at a processor, and a plurality of anonymized advertiser-user identifiers are received from an advertiser at the processor. Without de-anonymizing any publisher-user identifiers in the received plurality of publisher-user identifiers and any advertiser-user identifiers in the received plurality of advertiser-user identifiers, the processor obliviously computes an intersection among the received publisher-user identifiers and the received ad-user identifiers to create an intersection set containing a plurality of advertiser-user identifiers matched with publisher-user identifiers.

Delivering an advertisement is disclosed. Local user information is collected. Examples of local user information include language settings, web browser history, and actions taken by a user with respect to various applications. An advertisement is selected from a plurality of advertisements based at least in part on the local user information. The selected advertisement is caused to be displayed.

Various embodiments request discount offers on a mobile device within a store. In one embodiment, the mobile device detects it is being shaken and in response, sends a request for a discount offer to a server. The mobile device determines its location within the store. The mobile device receives a discount offer based on the location of the mobile device within the store and information associated with the mobile device. The discount offer is displayed and feedback is communicated to the server based on the detected device movement. The feedback is an indicator that indicates acceptance, rejection or a request for a different discount offer. The detected device movement include at least one of motion intensity, direction of motion and number of shakes. If the motion intensity of being shaken is greater than a predetermined threshold, an indication of objection is emitted.

The disclosure provides systems and methods for analysis of financial data and customization of financial products. Time-dependent data is obtained for a relatively large set of users, and from the data are determined a relatively small set of trajectories that model user behaviour. New users are characterized according to the trajectories and financial products are automatically personalised to suit the new user.

Methods, systems, and devices for displaying advertisements on mobile telephone devices at the end of a call to a pre-designated number are disclosed. In aspect a computerized method comprises determining that a telephone call has been initiated between a mobile telephone device and a second telephone device, determining that the telephone number matches a campaign telephone number stored on the mobile telephone device, determining a media object to display based on the telephone number, downloading the media object on the mobile telephone device, determining that the telephone call has ended, and displaying the media object on the mobile telephone device after the telephone call has ended.