Abstract: Aspects relate to delivering directed content using frequency capping concepts without third-party cookie technology or other user-identifiable information. Systems and methods are described for determining an estimated number of impressions a user may view or experience based on historical, anonymized data. A covisitation graph is used to estimate the number of times an unidentified user may see an item of directed content, within in a predetermined period of time, based on a single visit to a particular website. The covisitation graph accounts for and also provides for estimated views of the item of directed content on other websites deemed related to the particular website. Therefore the estimated delivery rate for that website can be calculated and used to enforce frequency capping principals.

Abstract: Aspects of the subject disclosure may include, for example, receiving information defining an attribute of interest for the impression, wherein the attribute of interest comprises a plurality of categories of values, and receiving information defining a respective probability for each respective value of the plurality of categories of values for the impression. Further, information about current values of the plurality of categories for the attribute of interest may be received and a pacing value may be determined based on the respective probability for each respective value of the plurality of categories of values, along with the information about current values the plurality of categories for the attribute of interest. A respective bid value of a bid may be adjusted using the pacing value and the adjusted bid value may be used in an auction to fill the impression. This permits automatic detection and correction of an inadvertent skew introduced when serving ads and other content.

Abstract: Aspects of the subject disclosure may include, for example, receiving from a campaign manager device information defining a line item in an online advertising system, including receiving information defining constraints for the line item. The subject disclosure may further include collecting browsing history information for targetable users matching the constraints for the line item, generating a machine learning model to rank the targetable users and building a new segment based on users ranked by the model. The subject disclosure may further include providing, to the campaign manager device, a recommendation to add the new segment to the line item, receiving from the campaign manager device an indication to attach the new segment to the line item, and subsequently, providing advertisement content to targeted users according to the line item including the new segment. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, receiving from a campaign manager device information defining a line item in an online advertising system, including receiving information defining constraints for the line item. The subject disclosure may further include collecting browsing history information for targetable users matching the constraints for the line item, generating a machine learning model to rank the targetable users and building a new segment based on users ranked by the model. The subject disclosure may further include providing, to the campaign manager device, a recommendation to add the new segment to the line item, receiving from the campaign manager device an indication to attach the new segment to the line item, and subsequently, providing advertisement content to targeted users according to the line item including the new segment. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, receiving from a campaign manager device information defining a line item in an online advertising system, including receiving information defining constraints for the line item. The subject disclosure may further include collecting browsing history information for targetable users matching the constraints for the line item, generating a machine learning model to rank the targetable users and building a new segment based on users ranked by the model. The subject disclosure may further include providing, to the campaign manager device, a recommendation to add the new segment to the line item, receiving from the campaign manager device an indication to attach the new segment to the line item, and subsequently, providing advertisement content to targeted users according to the line item including the new segment. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, receiving information defining an attribute of interest for the impression, wherein the attribute of interest comprises a plurality of categories of values, and receiving information defining a respective probability for each respective value of the plurality of categories of values for the impression. Further, information about current values of the plurality of categories for the attribute of interest may be received and a pacing value may be determined based on the respective probability for each respective value of the plurality of categories of values, along with the information about current values the plurality of categories for the attribute of interest. A respective bid value of a bid may be adjusted using the pacing value and the adjusted bid value may be used in an auction to fill the impression. This permits automatic detection and correction of an inadvertent skew introduced when serving ads and other content.