Abstract: Embodiments of the invention generate metrics quantifying the mobility of a mobile device without persisting information related to the device's specific location at any given time. Specifically, at multiple intervals, a value of a mobility metric is computed based on the distance between the current location of the mobile device and a previously identified origin location of the mobile device.

Abstract: Embodiments of the invention generate metrics quantifying the mobility of a mobile device without persisting information related to the device's specific location at any given time. Specifically, at multiple intervals, a value of a mobility metric is computed based on the distance between the current location of the mobile device and a previously identified origin location of the mobile device. The values of the mobility metric computed over a period of time quantify the overall mobility of the mobile device. The mobility metric does not provide any information regarding the specific location of the mobile device at any given time.

Abstract: Embodiments of the invention generate metrics quantifying the mobility of a mobile device without persisting information related to the device's specific location at any given time. Specifically, at multiple intervals, a value of a mobility metric is computed based on the distance between the current location of the mobile device and a previously identified origin location of the mobile device. The values of the mobility metric computed over a period of time quantify the overall mobility of the mobile device. The mobility metric does not provide any information regarding the specific location of the mobile device at any given time.

Abstract: Models are built based on existing histories in one identifier space to infer features of entities in a different identifier space. A source model is built using features of an archetypical population in a given identifier space and the standard population. A join panel, i.e., a set of entities operating across both the given identifier space and a second disjoined identifier space, is scored using the source model. Based on the scores and features associated with the entities in the join panel within the second identifier space, a target model specific to the second identifier space is built. An audience of entities within the second identifier space can then be scored using the target model to identify entities that are similar to the archetypical population.

Abstract: Embodiments of the invention generate metrics quantifying the mobility of a mobile device without persisting information related to the device's specific location at any given time. Specifically, at multiple intervals, a value of a mobility metric is computed based on the distance between the current location of the mobile device and a previously identified origin location of the mobile device. The values of the mobility metric computed over a period of time quantify the overall mobility of the mobile device. The mobility metric does not provide any information regarding the specific location of the mobile device at any given time.

Abstract: Embodiments of the invention generate metrics quantifying the mobility of a mobile device without persisting information related to the device's specific location at any given time. Specifically, at multiple intervals, a value of a mobility metric is computed based on the distance between the current location of the mobile device and a previously identified origin location of the mobile device. The values of the mobility metric computed over a period of time quantify the overall mobility of the mobile device. The mobility metric does not provide any information regarding the specific location of the mobile device at any given time.

Abstract: Embodiments of the invention generate metrics quantifying the mobility of a mobile device without persisting information related to the device's specific location at any given time. Specifically, at multiple intervals, a value of a mobility metric is computed based on the distance between the current location of the mobile device and a previously identified origin location of the mobile device. The values of the mobility metric computed over a period of time quantify the overall mobility of the mobile device. The mobility metric does not provide any information regarding the specific location of the mobile device at any given time.

Abstract: Embodiments of the invention generate metrics quantifying the mobility of a mobile device without persisting information related to the device's specific location at any given time. Specifically, at multiple intervals, a value of a mobility metric is computed based on the distance between the current location of the mobile device and a previously identified origin location of the mobile device. The values of the mobility metric computed over a period of time quantify the overall mobility of the mobile device. The mobility metric does not provide any information regarding the specific location of the mobile device at any given time.

Abstract: Embodiments of the invention generate metrics quantifying the mobility of a mobile device without persisting information related to the device's specific location at any given time. Specifically, at multiple intervals, a value of a mobility metric is computed based on the distance between the current location of the mobile device and a previously identified origin location of the mobile device. The values of the mobility metric computed over a period of time quantify the overall mobility of the mobile device. The mobility metric does not provide any information regarding the specific location of the mobile device at any given time.

Abstract: Embodiments of the invention generate metrics quantifying the mobility of a mobile device without persisting information related to the device's specific location at any given time. Specifically, at multiple intervals, a value of a mobility metric is computed based on the distance between the current location of the mobile device and a previously identified origin location of the mobile device. The values of the mobility metric computed over a period of time quantify the overall mobility of the mobile device. The mobility metric does not provide any information regarding the specific location of the mobile device at any given time.

Abstract: Embodiments of the invention generate metrics quantifying the mobility of a mobile device without persisting information related to the device's specific location at any given time. Specifically, at multiple intervals, a value of a mobility metric is computed based on the distance between the current location of the mobile device and a previously identified origin location of the mobile device. The values of the mobility metric computed over a period of time quantify the overall mobility of the mobile device. The mobility metric does not provide any information regarding the specific location of the mobile device at any given time.

Abstract: Models are built based on existing histories in one identifier space to infer features of entities in a different identifier space. A source model is built using features of an archetypical population in a given identifier space and the standard population. A join panel, i.e., a set of entities operating across both the given identifier space and a second disjoined identifier space, is scored using the source model. Based on the scores and features associated with the entities in the join panel within the second identifier space, a target model specific to the second identifier space is built. An audience of entities within the second identifier space can then be scored using the target model to identify entities that are similar to the archetypical population.

Abstract: Embodiments of the invention generate metrics quantifying the mobility of a mobile device without persisting information related to the device's specific location at any given time. Specifically, at multiple intervals, a value of a mobility metric is computed based on the distance between the current location of the mobile device and a previously identified origin location of the mobile device. The values of the mobility metric computed over a period of time quantify the overall mobility of the mobile device. The mobility metric does not provide any information regarding the specific location of the mobile device at any given time.

Abstract: Embodiments of the invention generate metrics quantifying the mobility of a mobile device without persisting information related to the device's specific location at any given time. Specifically, at multiple intervals, a value of a mobility metric is computed based on the distance between the current location of the mobile device and a previously identified origin location of the mobile device. The values of the mobility metric computed over a period of time quantify the overall mobility of the mobile device. The mobility metric does not provide any information regarding the specific location of the mobile device at any given time.

Abstract: Embodiments of the invention generate metrics quantifying the mobility of a mobile device without persisting information related to the device's specific location at any given time. Specifically, at multiple intervals, a value of a mobility metric is computed based on the distance between the current location of the mobile device and a previously identified origin location of the mobile device. The values of the mobility metric computed over a period of time quantify the overall mobility of the mobile device. The mobility metric does not provide any information regarding the specific location of the mobile device at any given time.