Abstract: A computer system includes a computer device configured to communicate via a communication network to a plurality of user computer devices including a particular target user computer device of a target user. A processor is coupled to the computer device and has access to social network data and browser data of the target user. The processor is configured to provide dynamically determined targeted content to be communicated to the particular target user computer device. The processor implements a recommendation service that analyzes context of the target user based on browse history, behavior data, demographic information, and social network momentum data. The recommendation service includes a social momentum recommendation engine that provides targeted content based on social network momentum data that is independent of and distinct from the browser data of the target user.

Abstract: A computer system comprises a computer server configured to communicate via a communication network to user computer devices including a target user computer device of a target user. Coupled to the computer server is a processor having access to social network data, user browser data of the target user, relationship data, and content data. The processor is configured to provide dynamically determined targeted content to be communicated to the target user computer device. The processor implements a recommendation service configured to analyze context of the target user based on browse history of the target user computer device, behavior data of the target user, demographic information of the target user, and social network momentum data. The recommendation service includes a social momentum recommendation engine configured to recommend the targeted content based on an amount of social momentum of content independent of and distinct from the browser data of the target user.

Abstract: Methods of generating recommendations may include obtaining social network data from one or more network resources. Word relationships may be created between selected words in the social network data to produce relationship data. Advertisement or other asset recommendations may be generated for a target user by analyzing browse information of the target user to identify one or more words. Other words in the relationship data may be identified that are related to the words in the target user's browse information. One or more advertisements may be identified having at least one keyword that corresponds to the other words. At least a portion of these advertisements may be selected from a data repository to provide to the target user.

Abstract: Methods of generating recommendations may include obtaining social network data from one or more network resources. Word relationships may be created between selected words in the social network data to produce relationship data. Advertisement or other asset recommendations may be generated for a target user by analyzing browse information of the target user to identify one or more words. Other words in the relationship data may be identified that are related to the words in the target user's browse information. One or more advertisements may be identified having at least one keyword that corresponds to the other words. At least a portion of these advertisements may be selected from a data repository to provide to the target user.

Abstract: Methods of generating recommendations may include obtaining social network data from one or more network resources. Word relationships may be created between selected words in the social network data to produce relationship data. Advertisement or other asset recommendations may be generated for a target user by analyzing browse information of the target user to identify one or more words. Other words in the relationship data may be identified that are related to the words in the target user's browse information. One or more advertisements may be identified having at least one keyword that corresponds to the other words. At least a portion of these advertisements may be selected from a data repository to provide to the target user.

Abstract: Methods of generating recommendations may include obtaining social network data from one or more network resources. Word relationships may be created between selected words in the social network data to produce relationship data. Advertisement or other asset recommendations may be generated for a target user by analyzing browse information of the target user to identify one or more words. Other words in the relationship data may be identified that are related to the words in the target user's browse information. One or more advertisements may be identified having at least one keyword that corresponds to the other words. At least a portion of these advertisements may be selected from a data repository to provide to the target user.

Abstract: Methods of generating recommendations may include obtaining social network data from one or more network resources. Word relationships may be created between selected words in the social network data to produce relationship data. Advertisement or other asset recommendations may be generated for a target user by analyzing browse information of the target user to identify one or more words. Other words in the relationship data may be identified that are related to the words in the target user's browse information. One or more advertisements may be identified having at least one keyword that corresponds to the other words. At least a portion of these advertisements may be selected from a data repository to provide to the target user.

Abstract: Methods of generating recommendations may include obtaining social network data from one or more network resources. Word relationships may be created between selected words in the social network data to produce relationship data. Advertisement or other asset recommendations may be generated for a target user by analyzing browse information of the target user to identify one or more words. Other words in the relationship data may be identified that are related to the words in the target user's browse information. One or more advertisements may be identified having at least one keyword that corresponds to the other words. At least a portion of these advertisements may be selected from a data repository to provide to the target user.

Abstract: Methods of generating recommendations may include obtaining social network data from one or more network resources. Word relationships may be created between selected words in the social network data to produce relationship data. Advertisement or other asset recommendations may be generated for a target user by analyzing browse information of the target user to identify one or more words. Other words in the relationship data may be identified that are related to the words in the target user's browse information. One or more advertisements may be identified having at least one keyword that corresponds to the other words. At least a portion of these advertisements may be selected from a data repository to provide to the target user.

Abstract: Methods of generating recommendations may include obtaining social network data from one or more network resources. Word relationships may be created between selected words in the social network data to produce relationship data. Advertisement or other asset recommendations may be generated for a target user by analyzing browse information of the target user to identify one or more words. Other words in the relationship data may be identified that are related to the words in the target user's browse information. One or more advertisements may be identified having at least one keyword that corresponds to the other words. At least a portion of these advertisements may be selected from a data repository to provide to the target user.

Abstract: Methods of generating recommendations may include obtaining social network data from one or more network resources. Word relationships may be created between selected words in the social network data to produce relationship data. Advertisement or other asset recommendations may be generated for a target user by analyzing browse information of the target user to identify one or more words. Other words in the relationship data may be identified that are related to the words in the target user's browse information. One or more advertisements may be identified having at least one keyword that corresponds to the other words. At least a portion of these advertisements may be selected from a data repository to provide to the target user.