Abstract: Methods, systems, and media for determining an index of a segment are disclosed. A first value representing one or more first users in a segment that have performed one or more key events may be determined. A second value representing one or more second users of a population that have performed the one or more key events may be determined. A third value representing one or more third users in the segment that have not performed the one or more key events may be determined. A fourth value representing one or more fourth users of the population that have not performed the one or more key events may be determined. The index for the segment may be calculated based on the first value, the second value, the third value, and the fourth value. The index may be transmitted.

Abstract: In a network comprising number of web sites and at least one simulator web page calls are simulated or monitored and the response to the calls, including content, re-directed calls and cookies are examined in order to identify whether the content of cookies has been written or modified illegally. Illegal modification of content of cookies is referred to as writing of data by a Buyer in cookies of a User that was directed to the Buyer by a Data Publisher, without the consent of the Data Publisher. In some embodiments when illegal cookies are identified an alert may be issued to a user.

Abstract: Methods, system, and media for scaling a panel of users with known attributes to determine an unknown attribute of a user are disclosed. An unclassified attribute vector of the user may be received. The unclassified attribute vector may comprise first attributes and first attribute values. A reduced attribute vector may be produced using the unclassified attribute vector and a projection matrix. The reduced attribute vector may have fewer attributes than the unclassified attribute vector. A plurality of reduced panel attribute vectors may be produced using a plurality of classified panel attribute vectors of users from the panel and the projection matrix. The reduced panel attribute vectors may have fewer attributes than the classified panel attribute vectors. The unknown attribute of the user may be determined based on the reduced attribute vector, the plurality of reduced panel attribute vectors, and the known attributes.

Abstract: System and method for automatic definition and tuning of user segment combinations used for targeted advertisement and marketing. Automated analysis and feedback modules may provide, ad hoc, optimized market segments definitions that maximize the conversion ratio for advertisements. The system and method may optimize of segment data based on a learning-running process built around a data exchange within a real-time bidding (RTB) media exchange system. In identifying qualified combinations for segments on-going loops or iterations may analyze the correlation between the performance of an advertisement or “creative” and user data, based on a set of parameters. As a part of data segmentation, embodiments of the present invention find combinations of parameters that may predict lift. Segment combinations are optimized by, for example combining a segment combination with one or more other segment combinations and/or dividing a segment combination into two or more different combinations.

Abstract: A targeting rule set of association rules may be created. A plurality of association rules may be selected. A plurality of candidate rule sets may be constructed based on the plurality of association rules. The plurality of candidate rule sets may be evaluated to produce metrics. One of the plurality of candidate rule sets may be assigned as the targeting rule set based on the metrics. A custom list of user may be formed using association rules. A user may be determined to belong to a segment by applying one or more rules of a targeting rule set to user attribute data. A custom list of cookies to show advertising may be formed using combinations of association rules.

Abstract: A method, system, and medium for managing modeled audience extension information that includes receiving tag information, the tag information comprising a user identifier corresponding to a user, a tag identifier, and one or more data values; adding the tag identifier and the one or more data values to a user object, wherein the user object is identified by the user identifier; assigning the user object to a segment based on the user object and a model, wherein the segment is identified by a segment identifier; and distributing the segment identifier and the user identifier to a market information buyer.