Abstract: Some embodiments described herein relate to receiving obfuscated location data associated with a first compute device, such as a mobile phone. A database including records of multiple compute devices, including a second compute device, associated with multiple obfuscated locations can be accessed and a link between the first compute device and the second compute device can be defined based, at least in part on the obfuscated location data associated with the first compute device matching a record for the second compute device. In some embodiments, the first compute device and/or the second compute device can receive content based, at least in part on the link.

Abstract: Some embodiments described herein relate to a method that includes surveying and/or passively monitoring content consumption by mobile communication devices. Each signal received from a mobile communication device can be associated with a common location. For example, an out-of-home device positioned at the location can be operable to receive requests from mobile communication devices that represent requests to access network locations. An audience profile for that common location can be defined based on a network location that is identified as being statistically overrepresented. Content targeted to the audience profile at the common location can then be provided.

Abstract: Some embodiments described herein relate to a method that includes surveying and/or passively monitoring content consumption by mobile communication devices. Each signal received from a mobile communication device can be associated with a common location. For example, an out-of-home device positioned at the location can be operable to receive requests from mobile communication devices that represent requests to access network locations. An audience profile for that common location can be defined based on a network location that is identified as being statistically overrepresented. Content targeted to the audience profile at the common location can then be provided.

Abstract: Some embodiments described herein relate to a method that includes surveying and/or passively monitoring content consumption by mobile communication devices. Each signal received from a mobile communication device can be associated with a common location. For example, an out-of-home device positioned at the location can be operable to receive requests from mobile communication devices that represent requests to access network locations. An audience profile for that common location can be defined based on a network location that is identified as being statistically overrepresented. Content targeted to the audience profile at the common location can then be provided.

Abstract: Some embodiments described herein relate to a method that includes surveying and/or passively monitoring content consumption by mobile communication devices. Each signal received from a mobile communication device can be associated with a common location. For example, an out-of-home device positioned at the location can be operable to receive requests from mobile communication devices that represent requests to access network locations. An audience profile for that common location can be defined based on a network location that is identified as being statistically overrepresented. Content targeted to the audience profile at the common location can then be provided.

Abstract: Some embodiments described herein relate to a method that includes surveying and/or passively monitoring content consumption by mobile communication devices. Each signal received from a mobile communication device can be associated with a common location. For example, an out-of-home device positioned at the location can be operable to receive requests from mobile communication devices that represent requests to access network locations. An audience profile for that common location can be defined based on a network location that is identified as being statistically overrepresented. Content targeted to the audience profile at the common location can then be provided.

Abstract: A non-transitory processor-readable medium is provided that stores code representing instructions to be executed by a processor to receive data associated with access by a first plurality of entities to a first website location and to receive data associated with access by a second plurality of entities to a second website location. The processor is also caused to define a co-visitation factor for each of the first website location and the second website location based on the received data. The processor is also caused to, if the co-visitation factor of the first website location and/or the co-visitation factor of the second website location is over a predefined threshold, select the first website location and/or the second website location as target website locations. The processor is caused to send a signal to set a flag associated with each target website location indicating the target website location as a suspicious website location.

Abstract: A complete end-to-end modeling system is provided that includes data sampling, feature engineering, action labeling, and model learning or learning from models built based on collected data. The end-to-end modeling process is performed via an automatic mechanism with minimal or reduced human intervention. A processor-readable medium is disclosed, storing processor-executable instructions to instantiate an automated data sampling and prediction structure training component, the automated data sampling and prediction structure training component being configured to automatically collect user event data samples, and use the collected user event data samples to train multiple prediction structures in parallel.

Abstract: Some embodiments described herein relate to receiving obfuscated location data associated with a first compute device, such as a mobile phone. A database including records of multiple compute devices, including a second compute device, associated with multiple obfuscated locations can be accessed and a link between the first compute device and the second compute device can be defined based, at least in part on the obfuscated location data associated with the first compute device matching a record for the second compute device. In some embodiments, the first compute device and/or the second compute device can receive content based, at least in part on the link.

Abstract: A complete end-to-end modeling system is provided that includes data sampling, feature engineering, action labeling, and model learning or learning from models built based on collected data. The end-to-end modeling process is performed via an automatic mechanism with minimal or reduced human intervention. A processor-readable medium is disclosed, storing processor-executable instructions to instantiate an automated data sampling and prediction structure training component, the automated data sampling and prediction structure training component being configured to automatically collect user event data samples, and use the collected user event data samples to train multiple prediction structures in parallel.

Abstract: A non-transitory processor-readable medium is provided that stores code representing instructions to be executed by a processor to receive data associated with access by a first plurality of entities to a first website location and to receive data associated with access by a second plurality of entities to a second website location. The processor is also caused to define a co-visitation factor for each of the first website location and the second website location based on the received data. The processor is also caused to, if the co-visitation factor of the first website location and/or the co-visitation factor of the second website location is over a predefined threshold, select the first website location and/or the second website location as target website locations. The processor is caused to send a signal to set a flag associated with each target website location indicating the target website location as a suspicious website location.

Abstract: A complete end-to-end modeling system is provided that includes data sampling, feature engineering, action labeling, and model learning or learning from models built based on collected data. The end-to-end modeling process is performed via an automatic mechanism with minimal or reduced human intervention. A processor-readable medium is disclosed, storing processor-executable instructions to instantiate an automated data sampling and prediction structure training component, the automated data sampling and prediction structure training component being configured to automatically collect user event data samples, and use the collected user event data samples to train multiple prediction structures in parallel.

Abstract: A non-transitory processor-readable medium stores code representing instructions to be executed by a processor to receive data associated with access by a first plurality of entities to a first website location and to receive data associated with access by a second plurality of entities to a second website location. The processor is also caused to define a co-visitation factor for each of the first website location and the second website location based on the received data. The processor is also caused to, if the co-visitation factor of the first website location and/or the co-visitation factor of the second website location is over a predefined threshold, select the first website location and/or the second website location as target website locations. The processor is caused to send a signal to set a flag associated with each target website location indicating the target website location as a suspicious website location.

Abstract: A non-transitory processor-readable medium stores code representing instructions to be executed by a processor to receive data associated with access by a first plurality of entities to a first website location and to receive data associated with access by a second plurality of entities to a second website location. The processor is also caused to define a co-visitation factor for each of the first website location and the second website location based on the received data. The processor is also caused to, if the co-visitation factor of the first website location and/or the co-visitation factor of the second website location is over a predefined threshold, select the first website location and/or the second website location as target website locations. The processor is caused to send a signal to set a flag associated with each target website location indicating the target website location as a suspicious website location.

Abstract: Methods for bid optimization and inventory scoring are provided. The method comprises receiving a definition of a success event associated with a campaign that has a set of campaign parameters. The method also comprises calculating an impact estimate for a performance measure of the success event. The impact estimate is calculated based on a set of auction parameters and a set of historical data associated with a browser. The method further comprises defining a bidding function based on the impact estimate, a set of characteristics of the browser, and the set of campaign parameters. The method also comprises calculating, after calculating the impact estimate and defining the bidding function, a bid value using the bidding function. The method also comprises sending a signal having the bid value to a real-time bidding exchange.

Abstract: Privacy-sensitive methods, systems, and media for targeting online advertisements using brand affinity modeling are provided.