Abstract: The present teaching relates to method, system, and medium for determining audience clusters to be assigned to an advertisement exposure opportunity. A plurality of advertisement exposure opportunities are obtained, wherein each of the plurality of advertisement exposure opportunities is to be used for placing an advertisement. For each of the plurality of advertisement exposure opportunities, a plurality of audience clusters are generated based on at least one criterion associated with the advertisement exposure opportunity. The plurality of audience clusters are ranked based on at least one ranking criterion, and ordered audience clusters are generated based on the ranking. The ordered audience clusters associated with the plurality of advertisement exposure opportunities in response to an event are updated, wherein the ordered audience clusters for each of the plurality of advertisement exposure opportunities are generated prior to receiving a request for placing the advertisement.

Abstract: The present teaching relates to method, system, and medium for profiling accounts. A plurality of identifiers are obtained, wherein each of the plurality of identifiers is associated with one of a device operated by a user and a platform on which the user consumes content in one or more media types. An account corresponding to the user is created, wherein the account represents the user across devices, platforms, and/or media types. A persistent identifier is generated for the account, wherein the persistent identifier links the plurality of identifiers. Consumption data related to the account with the persistent identifier is obtained. The consumption data is gathered from sources associated with the plurality of identifiers across different devices, platforms, or media types, and the account is profiled based on the obtained consumption data.

Abstract: The present teaching relates to method, system, and medium for profiling accounts. A plurality of identifiers are obtained, wherein each of the plurality of identifiers is associated with one of a device operated by a user and a platform on which the user consumes content in one or more media types. An account corresponding to the user is created, wherein the account represents the user across devices, platforms, and/or media types. A persistent identifier is generated for the account, wherein the persistent identifier links the plurality of identifiers. Consumption data related to the account with the persistent identifier is obtained. The consumption data is gathered from sources associated with the plurality of identifiers across different devices, platforms, or media types, and the account is profiled based on the obtained consumption data.

Abstract: Methods, systems, and programming for recommending targeted television programs based on online behavior is provided. In one example, information related to one or more online activities of a user is received. An identifier associated with the user is determined. Information related to television consumption of the user is assessed based on the identifier. An index is generated based on the online activity information and the television consumption information. One or more recommendations are generated based on the index.

Abstract: The present teaching relates to method, system, and medium for profiling accounts. A plurality of identifiers are obtained, wherein each of the plurality of identifiers is associated with one of a device operated by a user and a platform on which the user consumes content in one or more media types. An account corresponding to the user is created, wherein the account represents the user across devices, platforms, and/or media types. A persistent identifier is generated for the account, wherein the persistent identifier links the plurality of identifiers. Consumption data related to the account with the persistent identifier is obtained. The consumption data is gathered from sources associated with the plurality of identifiers across different devices, platforms, or media types, and the account is profiled based on the obtained consumption data.

Abstract: The present teaching relates to method, system, and medium for obtaining consumption data. A first request is received to retrieve a plurality of data sets, each of which is related to one of a plurality of accounts in an audience cluster, each account is represented by a persistent identifier that links multiple identifiers associated with one or more devices, or platforms on which content is consumed in at least one media type. Information related to content consumption on a device/platform associated with each of the linked multiple identifiers of the account is retrieved, and a data set of the account is provided based on information retrieved with respect to each of the linked multiple identifiers. The data set is presented in one representation upon a request for information about the account and retrieved data sets are provided in response to the first request, for forecasting performance of audience clusters.

Abstract: The present teaching relates to method, system, and medium for predicting performance of an audience cluster. First information related to a plurality of users in the audience cluster is received. A plurality of advertisements are received that are previously placed at an advertisement exposure opportunity and presented to the plurality of users, wherein each of the plurality of advertisements placed at the advertisement exposure opportunity is associated with first criteria. Second information related to events involving the plurality of users with respect to the plurality of advertisements is obtained and performance of the audience cluster associated with the advertisement exposure opportunity is predicted based on the obtained first information and second information in accordance with at least one prediction model and with respect to the first criteria.

Abstract: The present teaching relates to method, system, and medium for allocating advertisements. An advertisement associated with first criteria is received. A plurality of advertisement exposure opportunities are obtained, wherein each of the plurality of advertisement exposure opportunities is associated with second criteria and ordered audience clusters that are previously generated for the advertisement exposure opportunity. A predicted performance of each of the ordered audience clusters associated with each of the plurality of advertisement exposure opportunities is obtained, wherein the predicted performance is estimated with respect to the first criteria. At least one audience cluster is identified that is associated with one or more advertisement exposure opportunities based on the first and second criteria as well as the predicted performance associated with the ordered audience clusters of the plurality of advertisement exposure opportunities.

Abstract: The present teaching relates to method, system, and medium for determining audience clusters to be assigned to an advertisement exposure opportunity. A plurality of advertisement exposure opportunities are obtained, wherein each of the plurality of advertisement exposure opportunities is to be used for placing an advertisement. For each of the plurality of advertisement exposure opportunities, a plurality of audience clusters are generated based on at least one criterion associated with the advertisement exposure opportunity. The plurality of audience clusters are ranked based on at least one ranking criterion, and ordered audience clusters are generated based on the ranking. The ordered audience clusters associated with the plurality of advertisement exposure opportunities in response to an event are updated, wherein the ordered audience clusters for each of the plurality of advertisement exposure opportunities are generated prior to receiving a request for placing the advertisement.

Abstract: A computer system and method for list-based advertisement serving are provided. In at least one embodiment, a computer system or method may comprise creating advertisement lists before runtime based on list generation data, wherein each of the advertisement lists is associated with a respective target audience definition. The computer system or method may also comprise allocating advertisements among the advertisement lists before runtime, based on the list generation data, to cause each advertisement list to include a prioritized sequence of advertisements.

Abstract: Methods, systems, and programming for targeted advertising and conversion measurement. In one example, first information related to an online activity of a user is received. The online activity is associated with a first attribute to be used to identify the user. Second information related to an offline activity of the user is received. The offline activity is associated with a second attribute to be used to identify the user. A connection between the online activity and the offline activity of the user is then identified by matching the first attribute with the second attribute. A profile of the user is obtained based, at least in part, on the identified connection. A request of serving an advertisement is received. The user is selected from a plurality of users based on the profile of the user and information related to the request. The advertisement is provided to the user.

Abstract: Methods, systems, and programming for associating discrete user activities on mobile devices. In one example, first information related to a first online activity associated with a first user performed on a first mobile device is received. The first online activity relates to an exposure of an advertisement. A first identifier is generated for the first online activity based on an attribute related to the first mobile device. Second information related to a second online activity associated with a second user performed on a second mobile device is received. The second online activity relates to an event associated with the advertisement. A second identifier is generated for the second online activity based on the attribute related to the second mobile device. A connection between the first and second online activities associated with the advertisement is identified and recorded based on the first identifier and the second identifier.

Abstract: Methods, systems, and programming for advertisement conversion measurement. In one example, a request of serving an advertisement is received. The advertisement is provided to a user on a mobile device. A first identifier is generated based, at least in part, on an attribute related to the mobile device. Information related to a plurality of online activities that are associated with the advertisement is received. Each of the plurality of online activities is performed on a mobile device. A second identifier for each of the plurality of online activities is generated based, at least in part, on the attribute related to the corresponding mobile device. At least one online activity from the plurality of online activities is identified by matching the corresponding second identifier with the first identifier. A measure of serving the advertisement is determined based on the identified at least one online activity.

Abstract: Methods, systems, and programming for recommending targeted television programs based on online behavior is provided. In one example, information related to one or more online activities of a user is received. An identifier associated with the user is determined. Information related to television consumption of the user is assessed based on the identifier. An index is generated based on the online activity information and the television consumption information. One or more recommendations are generated based on the index.

Abstract: A computer system and method for list-based advertisement serving are provided. In at least one embodiment, a computer system or method may comprise creating advertisement lists before runtime based on list generation data, wherein each of the advertisement lists is associated with a respective target audience definition. The computer system or method may also comprise allocating advertisements among the advertisement lists before runtime, based on the list generation data, to cause each advertisement list to include a prioritized sequence of advertisements.