Disclosed is a computer implemented method of creating an audience list based on user behavior data. The method may include receiving, by a processor, filtering criteria for identifying the audience list. Further, the method may include filtering, by the processor, set of users based on the filtering criteria, wherein each user in the set of users is associated with user behavior data. Additionally, the method may include identifying, by the processor, a plurality of users from the set of users based on the filtering, wherein the plurality of users constitutes the audience list.

The present invention provides various systems and methods to intelligently predict the user's intent and persona based on derived hyper-contextual information from user's computing device and device-server ranking system to serve at least one search advertisement or at least one search string relevant to user's intent and persona at the time of user entering input or even before user entering input in the search editor of a computing-device application or webpage in real-time using a recommendation engine. The present invention suggests providing the recommendation engine implemented on the computing device that may enable the user to automatically perform hyper-contextual discovery and intelligently predict user's intent and persona and in response provide at least one search advertisement or at least one search string relevant to user intent.

Disclosed is a computer-implemented method for requesting and transmitting marketing images or video. The method includes receiving a communication from a remote terminal, identifying a user or a group of users that are associated with the received communication, identifying data associated with the identified user or the group of users, identifying goods or services using the identified data associated with the identified user or group of users, requesting marketing images or video from a marketing images or video supplying system that are relating to the identified goods or services, receiving the requested marketing images or video from the marketing images or video supplying system, and transmitting the received marketing images or video to the remote terminal.

Methods and systems for matching a consumer to benefits offered by enabling organizations provide flexibility and utility to consumers in the marketplace for various products. Information about benefits and enabling organizations are provided and stored in a memory of a computer system. A search query including consumer interest data of a consumer, or results of such a search query, are received. The enabling organization information, benefit information, and search query or information related to the search query results are analyzed automatically in the computer system to provide analysis results, to determine whether any enabling organization to which the consumer is affiliated is offering a benefit for the consumer that is applicable to the said consumer interest data. A message is sent to the consumer including a list of venues ordered according to a search score.

A computer-implemented method of providing one or more selected tracking tags to a domain owner server for deployment on a website is described. The one or more tracking tags are selected from a set of available tracking tags and the method comprises: storing the set of available tracking tags, each available tracking tag including a purpose parameter describing a use to which data collected by the available tracking tag will be put; storing a plurality of user identifiers and a plurality of sets of tag-selection parameters, each user identifier identifying a website user and having an associated set of tag-selection parameters which identity a specific tracking tag and indicate whether a user consent has been obtained for a specific purpose of the specific tag; receiving, from the domain owner server, a request for deployment of one or more tracking tags on the website, the request including a received user identifier identifying a user accessing the website; for a user identifier corresponding to the received user identifier, comparing the tag-parameters for each specific tracking tag to the purpose parameter of each corresponding available tracking tag; selecting available tracking tags where the purpose parameter of the available tracking tag corresponds to a specific purpose which has an indication of user consent in the corresponding tag-selection parameters; and transmitting the selected available tracking tags to the domain owner server for deployment on the website.

The present disclosure discloses a method and device for pushing information to a target user. One example method includes identifying a plurality of users that meet a predetermined condition; selecting a target user from the identified users to be provided with information, where in the target user is selected based on a relationship strength and an influence of the identified users; and transmitting the information to the determined target user over a network, and relates to the field of information technologies.

Methods, systems, and apparatus include computer programs encoded on a computer-readable storage medium, including a method for providing content. A linking is provided of identifiers for users or devices known to a content delivery service. Each identifier is associated with the user or device in a specific context. The linking includes first and second identifiers. A request for content is received that includes either the first or second identifier. Bidders in an exchange are identified that have expressed an interest in bidding on a content delivery opportunity associated with the user or the device. For each bidder, a relative value is determined for a respective bidder for the opportunity to present content to the user or device in association with each identifier known to the bidder. For each bidder, a real-time bid request is generated in the exchange that includes the highest value identifier for submission to a respective bidder.

The application relates to a video recommendation method and device, and a computer readable storage medium. The video recommendation method comprises: obtaining a user feature of a sample user and a video feature of a sample video; learning a click rate, a like rate, and a follow rate on the basis of a full-connection neural network algorithm to obtain trained user feature and video feature; performing, according to the trained user feature and video feature, combined learning on the click rate, the like rate, and the follow rate on a user side neural network and a video side neural network; and obtaining a video recommendation list according to a network parameter of a neural network algorithm obtained by means of combined learning. According to the video recommendation method, by adding a full-connection neural network algorithm training phase, the trained user feature and video feature are obtained.

A method, system, and non-transitory computer readable medium for an advertisement distribution system, include calculating an interest for each advertisement of an advertisement group, assigning each advertisement a user engagement value based on the interest, conducting an auction to determine winning advertisements based on advertiser parameters received from a database and the user engagement value of each of the plurality of advertisements, and dynamically populating an unviewed portion of the web page with the advertisement group of the winning advertisements.

A mobile telephone or tablet or the like (40) for viewing commercial television programmes has a display screen (41), a firewall (70), and behind the firewall a first, sealed data storage section (42) which stores personal attributes of a viewer, such as a child, supplied on a token (32) from a trusted third party (10), a second, unsealed data storage section (44) to which the personal attributes are copied, the second section having a flag (48) which is set when the data in the second section has been modified by the viewer, and a third data storage section (46) in which personal preferences can be stored by the viewer. Adverts from advertisers (50) targeted on the data in the second and third sections are sent to the device (40), headers in the adverts are checked against the data in the first section, and adverts are rejected if they are unsuitable for the viewer. Unrejected adverts are shown on the display screen, and the advertiser is informed of their showing, but the identity of the viewer is not disclosed.